------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\mbeissin\Desktop\Stata files for book\Logfiles\chapter7.log
  log type:  text
 opened on:  25 Jan 2022, 22:17:15

. * ============================================================================
. * STATISTICAL RESULTS APPEARING IN CHAPTER 7
. * STATA Do file for Chapter 7  
. * Results reported in Chapter 7  
. * Author: Mark R. Beissinger  
. * Date:  January 2022  
. * Princeton, NJ 
. * =============================================================================
. * BEFORE RUNNING, YOU MUST SET THE DEFAULT PATH FOR WHERE THE DATA
. *   FILES RESIDE
. * =============================================================================
. * Before running, you must download the following package for STATA for running 
. *  Brant tests (the brant command within the following package):
. *    spost13_ado from https://jslsoc.sitehost.iu.edu/stata
. * =============================================================================
. * The following datafiles are used in this chapter:
. *   Monitoring surveys (Ukraine)--monitoring20052014engmerged.dta
. *   KIIS survey (Ukraine)--mohyla.orangerev.dta
. *   2011 Arab Barometer--Tunisia and Egypt--fullarabbarom2.dta
. *   Cross-sectional data on revolutionary episodes--revolutionaryeps.dta
. *   NOTE: The Gallup and Doherty/Schraeder data cited in this chapter are not 
. *      available for replication purposes; readers interested in these data 
. *      must consult the Gallup Organization and Doherty/Schraeder directly
. * =============================================================================
. * Output produced:  Logfiles\chapter7.log
. * =============================================================================
. 
. 
. * ====================
. * DATA FOR FIGURE 7.1
. * ====================
. use monitoring20052014engmerged.dta

. tab partic6 if EVA_vers=="yr2005", m

Part/Aid/Su |
pport/Apath |
etic/Oppose |
   /Counter |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        280       15.56       15.56
    Aid rev |         58        3.22       18.78
Support rev |        651       36.17       54.94
  Apathetic |        154        8.56       63.50
 Oppose rev |        567       31.50       95.00
 Countermob |         37        2.06       97.06
          . |         53        2.94      100.00
------------+-----------------------------------
      Total |      1,800      100.00

. tab partic6 if EVA_vers=="yr2014", m

Part/Aid/Su |
pport/Apath |
etic/Oppose |
   /Counter |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        155        8.61        8.61
    Aid rev |        135        7.50       16.11
Support rev |        724       40.22       56.33
  Apathetic |        223       12.39       68.72
 Oppose rev |        499       27.72       96.44
 Countermob |         17        0.94       97.39
          . |         47        2.61      100.00
------------+-----------------------------------
      Total |      1,800      100.00

. 
. * ====================
. * DATA FOR FIGURE 7.2
. * ====================
. clear

. use fullarabbarom2.dta

. tab egpartic6 if country==2, m

            Egypt: |
Part/Aid/Supp/Apat |
  h/Oppose/Counter |      Freq.     Percent        Cum.
-------------------+-----------------------------------
       Participate |         90        7.38        7.38
               Aid |         28        2.30        9.68
           Support |        834       68.42       78.10
Apathetic/inactive |         82        6.73       84.82
            Oppose |        169       13.86       98.69
           Counter |          8        0.66       99.34
                 . |          8        0.66      100.00
-------------------+-----------------------------------
             Total |      1,219      100.00

. tab tpartic5 if country==10, m

             Tunisia: |
Part/Supp/Apath/Opp/C |
               ounter |      Freq.     Percent        Cum.
----------------------+-----------------------------------
          Participate |        171       14.30       14.30
              Support |        812       67.89       82.19
   Apathetic/inactive |        132       11.04       93.23
               Oppose |         18        1.51       94.73
Counter-revolutionary |         21        1.76       96.49
                    . |         42        3.51      100.00
----------------------+-----------------------------------
                Total |      1,196      100.00

. 
. * =================================================================
. * PREFERENCE FALSIFICATION: COMPARISON OF MONITORING AND KIIS DATA
. * =================================================================
. clear

. use mohyla.orangerev.dta

. tab demopartvote, m

      Protest & vote |
  intention crosstab |      Freq.     Percent        Cum.
---------------------+-----------------------------------
   Orange demo, vote |        277       13.55       13.55
Orange vote, no demo |        550       26.91       40.46
    No vote, no demo |        269       13.16       53.62
  Blue vote, no demo |        729       35.67       89.29
     Blue demo, vote |         82        4.01       93.30
                   . |        137        6.70      100.00
---------------------+-----------------------------------
               Total |      2,044      100.00

. * Comparison of whether supporters knew friends or relatives who participated
. tab demopartvote v24, row

+----------------+
| Key            |
|----------------|
|   frequency    |
| row percentage |
+----------------+

                     |   Did you or relatives/friends
                     |  participate in protests after
      Protest & vote |            2nd round?
  intention crosstab | Yes, I pe  I didn't   Neither I |     Total
---------------------+---------------------------------+----------
   Orange demo, vote |       277          0          0 |       277 
                     |    100.00       0.00       0.00 |    100.00 
---------------------+---------------------------------+----------
Orange vote, no demo |         0        278        272 |       550 
                     |      0.00      50.55      49.45 |    100.00 
---------------------+---------------------------------+----------
    No vote, no demo |         0         50        219 |       269 
                     |      0.00      18.59      81.41 |    100.00 
---------------------+---------------------------------+----------
  Blue vote, no demo |         0        134        595 |       729 
                     |      0.00      18.38      81.62 |    100.00 
---------------------+---------------------------------+----------
     Blue demo, vote |        82          0          0 |        82 
                     |    100.00       0.00       0.00 |    100.00 
---------------------+---------------------------------+----------
               Total |       359        462      1,086 |     1,907 
                     |     18.83      24.23      56.95 |    100.00 


. 
. * ============================================================================
. * PREFERENCE FALSIFICATION: ANTI-MAIDAN SUPPORT, REFUSAL TO ANSWER, BY REGION
. * ============================================================================
. clear

. use monitoring20052014engmerged.dta

. tab EVA310C donbas if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Did you support the |
       demands of the |
  participants in the |        Donbas
 Anti-Maidan actions? |        no        yes |     Total
----------------------+----------------------+----------
Supported from very b |        39         48 |        87 
                      |      2.62      17.08 |      4.91 
----------------------+----------------------+----------
Did not supp at begin |        19         10 |        29 
                      |      1.28       3.56 |      1.64 
----------------------+----------------------+----------
Supp at beginning, no |        33         12 |        45 
                      |      2.21       4.27 |      2.54 
----------------------+----------------------+----------
Did not supp then and |     1,084        111 |     1,195 
                      |     72.75      39.50 |     67.48 
----------------------+----------------------+----------
          Hard to say |       315        100 |       415 
                      |     21.14      35.59 |     23.43 
----------------------+----------------------+----------
                Total |     1,490        281 |     1,771 
                      |    100.00     100.00 |    100.00 


. logit antimaidnoanswer west eastnodon south donbas if EVA_vers=="yr2014", or

Iteration 0:   log likelihood = -964.23277  
Iteration 1:   log likelihood = -940.57565  
Iteration 2:   log likelihood = -940.11689  
Iteration 3:   log likelihood = -940.11666  
Iteration 4:   log likelihood = -940.11666  

Logistic regression                             Number of obs     =      1,771
                                                LR chi2(4)        =      48.23
                                                Prob > chi2       =     0.0000
Log likelihood = -940.11666                     Pseudo R2         =     0.0250

----------------------------------------------------------------------------------
antimaidnoanswer | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
            west |   .6853144   .1276673    -2.03   0.043      .475685    .9873253
       eastnodon |   1.643094    .255918     3.19   0.001     1.210834    2.229668
           south |   1.269144   .2502179     1.21   0.227     .8623676    1.867796
          donbas |   2.255985   .3630595     5.06   0.000     1.645701    3.092584
           _cons |    .244898   .0249437   -13.81   0.000     .2005798    .2990082
----------------------------------------------------------------------------------

. 
. * =====================================================================
. * DEGREE OF COMMITMENT TO DEFENDING THEIR VOTE AMONG REGIME SUPPORTERS 
. *   AND OPPOSITION SUPPORTERS, ORANGE REVOLUTION
. * =====================================================================
. clear

. use mohyla.orangerev.dta

. tab votefor defendchoice, chi row

+----------------+
| Key            |
|----------------|
|   frequency    |
| row percentage |
+----------------+

    Likely |
Yushchenko |   Willing to defend
        or |  choice in election
Yanukovych | through protest (V23)
     voter |        no        yes |     Total
-----------+----------------------+----------
Yushchenko |       168        623 |       791 
           |     21.24      78.76 |    100.00 
-----------+----------------------+----------
Yanukovych |       584        183 |       767 
           |     76.14      23.86 |    100.00 
-----------+----------------------+----------
     Total |       752        806 |     1,558 
           |     48.27      51.73 |    100.00 

          Pearson chi2(1) = 470.0680   Pr = 0.000

. 
. * ===============================================================
. * ILLUSTRATIONS OF WHAT ONE CAN LEARN--INITIAL FIGURES PRESENTED
. *   ON ORANGE REVOLUTION PARTICIPANTS
. * ===============================================================
. clear

. use monitoring20052014engmerged.dta

. * PARTICIPANTS VS. OTHERS
. * Living space
. ttest EVA242 if EVA_vers=="yr2005", by(newpartica)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
       0 |   1,439    42.79357     .686501    26.04184    41.44692    44.14022
       1 |     260      60.475    10.98098    177.0629    38.85164    82.09836
---------+--------------------------------------------------------------------
combined |   1,699    45.49938    1.782289    73.46403    42.00367     48.9951
---------+--------------------------------------------------------------------
    diff |           -17.68143    4.933383               -27.35758   -8.005274
------------------------------------------------------------------------------
    diff = mean(0) - mean(1)                                      t =  -3.5840
Ho: diff = 0                                     degrees of freedom =     1697

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0002         Pr(|T| > |t|) = 0.0003          Pr(T > t) = 0.9998

. 
. * Heating of home in winter
. ologit EVA247 gender newage newpartica if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -1719.3389  
Iteration 1:   log likelihood = -1705.9048  
Iteration 2:   log likelihood = -1705.8478  
Iteration 3:   log likelihood = -1705.8478  

Ordered logistic regression                     Number of obs     =      1,798
                                                LR chi2(3)        =      26.98
                                                Prob > chi2       =     0.0000
Log likelihood = -1705.8478                     Pseudo R2         =     0.0078

------------------------------------------------------------------------------
      EVA247 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.352849    .130853     3.12   0.002     1.119226    1.635238
      newage |    1.00307   .0028692     1.07   0.284     .9974621    1.008709
  newpartica |   1.703891   .2388896     3.80   0.000     1.294498    2.242757
-------------+----------------------------------------------------------------
       /cut1 |  -1.758809   .1605776                     -2.073535   -1.444082
       /cut2 |  -.1927976   .1516115                     -.4899507    .1043554
       /cut3 |   4.502112   .2397305                      4.032249    4.971975
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |       9.49      0.148       6
 -------------+------------------------------
       gender |       4.86      0.088       2
       newage |       0.47      0.789       2
   newpartica |       4.14      0.126       2

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,798
Model VCE    : OIM

1._predict   : Pr(EVA247==1), predict(pr outcome(1))
2._predict   : Pr(EVA247==2), predict(pr outcome(2))
3._predict   : Pr(EVA247==3), predict(pr outcome(3))
4._predict   : Pr(EVA247==4), predict(pr outcome(4))

1._at        : gender          =    .4427141 (mean)
               newage          =    45.55729 (mean)
               newpartica      =           0

2._at        : gender          =    .4427141 (mean)
               newage          =    45.55729 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1158587   .0079482    14.58   0.000     .1002805     .131437
        1 2  |   .0714146   .0096076     7.43   0.000     .0525841    .0902452
        2 1  |   .2696492   .0110339    24.44   0.000     .2480231    .2912753
        2 2  |   .1976942   .0178393    11.08   0.000     .1627298    .2326587
        3 1  |   .6001297   .0124241    48.30   0.000      .575779    .6244804
        3 2  |   .7066641   .0235698    29.98   0.000     .6604682      .75286
        4 1  |   .0143624    .002689     5.34   0.000     .0090921    .0196326
        4 2  |    .024227   .0051278     4.72   0.000     .0141766    .0342774
------------------------------------------------------------------------------

. 
. * Attends church
. logit attendschurch gender newage newpartica if EVA_vers=="yr2005", or 

Iteration 0:   log likelihood = -811.01018  
Iteration 1:   log likelihood = -776.27874  
Iteration 2:   log likelihood = -775.15717  
Iteration 3:   log likelihood =  -775.1558  
Iteration 4:   log likelihood =  -775.1558  

Logistic regression                             Number of obs     =      1,800
                                                LR chi2(3)        =      71.71
                                                Prob > chi2       =     0.0000
Log likelihood =  -775.1558                     Pseudo R2         =     0.0442

-------------------------------------------------------------------------------
attendschurch | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
       gender |    .589949   .0803104    -3.88   0.000      .451793    .7703524
       newage |    1.02501   .0040778     6.21   0.000     1.017049    1.033034
   newpartica |   2.283381   .3774755     4.99   0.000     1.651439    3.157142
        _cons |   .0654528   .0147249   -12.12   0.000     .0421147    .1017237
-------------------------------------------------------------------------------

. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,800
Model VCE    : OIM

Expression   : Pr(attendschurch), predict()

1._at        : gender          =    .4433333 (mean)
               newage          =    45.55444 (mean)
               newpartica      =           0

2._at        : gender          =    .4433333 (mean)
               newage          =    45.55444 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1376366   .0092092    14.95   0.000     .1195869    .1556863
          2  |   .2670967   .0281055     9.50   0.000      .212011    .3221825
------------------------------------------------------------------------------

. 
. * Smoker
. logit smoker gender newage newpartica if EVA_vers=="yr2005", or 

Iteration 0:   log likelihood = -1167.1621  
Iteration 1:   log likelihood = -947.28296  
Iteration 2:   log likelihood = -941.32026  
Iteration 3:   log likelihood = -941.29744  
Iteration 4:   log likelihood = -941.29744  

Logistic regression                             Number of obs     =      1,797
                                                LR chi2(3)        =     451.73
                                                Prob > chi2       =     0.0000
Log likelihood = -941.29744                     Pseudo R2         =     0.1935

------------------------------------------------------------------------------
      smoker | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   6.865551   .7987329    16.56   0.000     5.465719    8.623897
      newage |   .9610233   .0035189   -10.86   0.000     .9541511     .967945
  newpartica |   .7058207   .1094636    -2.25   0.025     .5208158    .9565435
       _cons |   1.241833   .2150496     1.25   0.211     .8844222     1.74368
------------------------------------------------------------------------------

. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,797
Model VCE    : OIM

Expression   : Pr(smoker), predict()

1._at        : gender          =     .443517 (mean)
               newage          =    45.54535 (mean)
               newpartica      =           0

2._at        : gender          =     .443517 (mean)
               newage          =    45.54535 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3230699   .0138801    23.28   0.000     .2958654    .3502744
          2  |   .2519775   .0274567     9.18   0.000     .1981633    .3057917
------------------------------------------------------------------------------

. 
. * True friends
. ologit newtruefriends gender newage newpartica if EVA_vers=="yr2005", or 

Iteration 0:   log likelihood = -1729.8949  
Iteration 1:   log likelihood = -1724.6746  
Iteration 2:   log likelihood = -1724.6661  
Iteration 3:   log likelihood = -1724.6661  

Ordered logistic regression                     Number of obs     =      1,752
                                                LR chi2(3)        =      10.46
                                                Prob > chi2       =     0.0151
Log likelihood = -1724.6661                     Pseudo R2         =     0.0030

--------------------------------------------------------------------------------
newtruefriends | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        gender |   .9667938   .0905507    -0.36   0.718     .8046548    1.161604
        newage |   1.000146   .0028031     0.05   0.958     .9946674    1.005655
    newpartica |   1.522634   .2028544     3.16   0.002     1.172718     1.97696
---------------+----------------------------------------------------------------
         /cut1 |  -1.000326   .1514359                     -1.297135   -.7035169
         /cut2 |  -.1722393   .1493719                     -.4650028    .1205243
--------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |       2.63      0.452       3
 -------------+------------------------------
       gender |       1.34      0.247       1
       newage |       0.06      0.801       1
   newpartica |       1.12      0.290       1

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,752
Model VCE    : OIM

1._predict   : Pr(newtruefriends==1), predict(pr outcome(1))
2._predict   : Pr(newtruefriends==2), predict(pr outcome(2))
3._predict   : Pr(newtruefriends==3), predict(pr outcome(3))

1._at        : gender          =    .4469178 (mean)
               newage          =    45.46575 (mean)
               newpartica      =           0

2._at        : gender          =    .4469178 (mean)
               newage          =    45.46575 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .2705395   .0113848    23.76   0.000     .2482257    .2928533
        1 2  |   .1958669   .0200235     9.78   0.000     .1566216    .2351123
        2 1  |   .1886017   .0095225    19.81   0.000     .1699378    .2072655
        2 2  |     .16209   .0116033    13.97   0.000      .139348    .1848319
        3 1  |   .5408589   .0129457    41.78   0.000     .5154857     .566232
        3 2  |   .6420431   .0283234    22.67   0.000     .5865302    .6975559
------------------------------------------------------------------------------

. 
. * Loneliness
. ologit EVA185 gender newage newpartica if EVA_vers=="yr2005", or 

Iteration 0:   log likelihood = -2507.6052  
Iteration 1:   log likelihood = -2487.1485  
Iteration 2:   log likelihood = -2487.1228  
Iteration 3:   log likelihood = -2487.1228  

Ordered logistic regression                     Number of obs     =      1,799
                                                LR chi2(3)        =      40.96
                                                Prob > chi2       =     0.0000
Log likelihood = -2487.1228                     Pseudo R2         =     0.0082

------------------------------------------------------------------------------
      EVA185 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   .6716148   .0584283    -4.58   0.000     .5663286    .7964747
      newage |    1.00458   .0026115     1.76   0.079     .9994751    1.009712
  newpartica |   .6739219   .0821815    -3.24   0.001     .5306518    .8558734
-------------+----------------------------------------------------------------
       /cut1 |  -.7236132   .1387497                     -.9955575   -.4516689
       /cut2 |   .6726111   .1375532                      .4030117    .9422104
       /cut3 |   1.937817   .1471416                      1.649425    2.226209
       /cut4 |   3.287032    .181481                      2.931336    3.642728
------------------------------------------------------------------------------

. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,799
Model VCE    : OIM

1._predict   : Pr(EVA185==1), predict(pr outcome(1))
2._predict   : Pr(EVA185==2), predict(pr outcome(2))
3._predict   : Pr(EVA185==3), predict(pr outcome(3))
4._predict   : Pr(EVA185==4), predict(pr outcome(4))
5._predict   : Pr(EVA185==5), predict(pr outcome(5))

1._at        : gender          =    .4435798 (mean)
               newage          =    45.56809 (mean)
               newpartica      =           0

2._at        : gender          =    .4435798 (mean)
               newage          =    45.56809 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .3196709   .0117498    27.21   0.000     .2966417    .3427002
        1 2  |   .4108038    .027603    14.88   0.000     .3567029    .4649048
        2 1  |   .3352949   .0112484    29.81   0.000     .3132484    .3573415
        2 2  |   .3271926   .0120691    27.11   0.000     .3035376    .3508476
        3 1  |   .2156197   .0100802    21.39   0.000     .1958629    .2353764
        3 2  |   .1709458   .0142123    12.03   0.000     .1430901    .1988014
        4 1  |   .0922797   .0070614    13.07   0.000     .0784397    .1061198
        4 2  |   .0657252   .0080053     8.21   0.000      .050035    .0814153
        5 1  |   .0371347   .0045598     8.14   0.000     .0281977    .0460718
        5 2  |   .0253327    .004088     6.20   0.000     .0173203     .033345
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |      39.20      0.000       9
 -------------+------------------------------
       gender |       2.56      0.465       3
       newage |      35.18      0.000       3
   newpartica |       0.77      0.857       3

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * failed Brant test--alternative results using mlogit
. mlogit EVA185 gender newage newpartica if EVA_vers=="yr2005", rrr b(3)

Iteration 0:   log likelihood = -2507.6052  
Iteration 1:   log likelihood = -2468.1803  
Iteration 2:   log likelihood = -2466.9281  
Iteration 3:   log likelihood = -2466.9228  
Iteration 4:   log likelihood = -2466.9228  

Multinomial logistic regression                 Number of obs     =      1,799
                                                LR chi2(12)       =      81.36
                                                Prob > chi2       =     0.0000
Log likelihood = -2466.9228                     Pseudo R2         =     0.0162

--------------------------------------------------------------------------------------------------
                          EVA185 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
Practically_never                |
                          gender |   1.539806   .2077438     3.20   0.001     1.182022    2.005886
                          newage |   1.009192   .0040762     2.27   0.023     1.001235    1.017213
                      newpartica |   1.775198   .3384493     3.01   0.003     1.221691     2.57948
                           _cons |   .8149208   .1697109    -0.98   0.326     .5418123    1.225694
---------------------------------+----------------------------------------------------------------
Sometimes                        |
                          gender |   1.365061    .184319     2.30   0.021     1.047653    1.778634
                          newage |   1.004893   .0040501     1.21   0.226     .9969859    1.012862
                      newpartica |   1.245769   .2460296     1.11   0.266     .8459247    1.834607
                           _cons |   1.092421   .2242636     0.43   0.667     .7305439    1.633554
---------------------------------+----------------------------------------------------------------
Time_to_time__not_often_not_rare |  (base outcome)
---------------------------------+----------------------------------------------------------------
Quite_often                      |
                          gender |   .8336138   .1676081    -0.91   0.365     .5621091    1.236258
                          newage |   1.027573    .005969     4.68   0.000     1.015941    1.039339
                      newpartica |   1.116978   .3359041     0.37   0.713     .6195353     2.01383
                           _cons |   .1244398   .0397509    -6.52   0.000     .0665354    .2327372
---------------------------------+----------------------------------------------------------------
Constantly                       |
                          gender |   .6738393   .2022927    -1.31   0.189      .374126    1.213654
                          newage |   1.038608   .0088273     4.46   0.000     1.021451    1.056054
                      newpartica |    .998007   .4631091    -0.00   0.997      .401927    2.478107
                           _cons |   .0310195   .0152725    -7.05   0.000      .011818    .0814191
--------------------------------------------------------------------------------------------------

. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,799
Model VCE    : OIM

1._predict   : Pr(EVA185==Practically_never), predict(pr outcome(1))
2._predict   : Pr(EVA185==Sometimes), predict(pr outcome(2))
3._predict   : Pr(EVA185==Time_to_time__not_often_not_rare), predict(pr outcome(3))
4._predict   : Pr(EVA185==Quite_often), predict(pr outcome(4))
5._predict   : Pr(EVA185==Constantly), predict(pr outcome(5))

1._at        : gender          =    .4435798 (mean)
               newage          =    45.56809 (mean)
               newpartica      =           0

2._at        : gender          =    .4435798 (mean)
               newage          =    45.56809 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .3250587   .0121996    26.65   0.000     .3011479    .3489695
        1 2  |   .4288495   .0301765    14.21   0.000     .3697047    .4879944
        2 1  |   .3400485   .0123278    27.58   0.000     .3158865    .3642106
        2 2  |   .3148289   .0281708    11.18   0.000     .2596152    .3700426
        3 1  |   .2170744   .0107496    20.19   0.000     .1960055    .2381433
        3 2  |   .1613262   .0221966     7.27   0.000     .1178218    .2048307
        4 1  |   .0860589   .0075187    11.45   0.000     .0713224    .1007954
        4 2  |   .0714392    .016261     4.39   0.000     .0395681    .1033103
        5 1  |   .0317595   .0048651     6.53   0.000     .0222241    .0412948
        5 2  |   .0235561   .0095444     2.47   0.014     .0048494    .0422628
------------------------------------------------------------------------------

. 
. * Satisfied with life as a whole
. ologit EVA130  gender newage newpartica if EVA_vers=="yr2005", or 

Iteration 0:   log likelihood = -2568.9818  
Iteration 1:   log likelihood = -2545.1917  
Iteration 2:   log likelihood = -2545.1579  
Iteration 3:   log likelihood = -2545.1579  

Ordered logistic regression                     Number of obs     =      1,800
                                                LR chi2(3)        =      47.65
                                                Prob > chi2       =     0.0000
Log likelihood = -2545.1579                     Pseudo R2         =     0.0093

------------------------------------------------------------------------------
      EVA130 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.118801   .0963034     1.30   0.192     .9451132    1.324409
      newage |   .9949987   .0025607    -1.95   0.051     .9899925     1.00003
  newpartica |   2.024879   .2417897     5.91   0.000     1.602351    2.558825
-------------+----------------------------------------------------------------
       /cut1 |  -2.025928   .1484329                     -2.316851   -1.735005
       /cut2 |  -.2957652   .1382664                     -.5667624   -.0247681
       /cut3 |   .8759141   .1398915                      .6017318    1.150096
       /cut4 |   3.554954   .1947501                      3.173251    3.936657
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |      12.39      0.192       9
 -------------+------------------------------
       gender |       2.56      0.464       3
       newage |       6.24      0.101       3
   newpartica |       1.76      0.623       3

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,800
Model VCE    : OIM

1._predict   : Pr(EVA130==1), predict(pr outcome(1))
2._predict   : Pr(EVA130==2), predict(pr outcome(2))
3._predict   : Pr(EVA130==3), predict(pr outcome(3))
4._predict   : Pr(EVA130==4), predict(pr outcome(4))
5._predict   : Pr(EVA130==5), predict(pr outcome(5))

1._at        : gender          =    .4433333 (mean)
               newage          =    45.55444 (mean)
               newpartica      =           0

2._at        : gender          =    .4433333 (mean)
               newage          =    45.55444 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1361913   .0085254    15.97   0.000     .1194819    .1529006
        1 2  |   .0722385    .008518     8.48   0.000     .0555435    .0889336
        2 1  |   .3345601   .0116491    28.72   0.000     .3117283    .3573918
        2 2  |   .2329653   .0172108    13.54   0.000     .1992327    .2666979
        3 1  |   .2708965   .0105161    25.76   0.000     .2502854    .2915077
        3 2  |   .2811811   .0112725    24.94   0.000     .2590875    .3032747
        4 1  |   .2350035   .0103944    22.61   0.000     .2146309    .2553762
        4 2  |   .3674418   .0234133    15.69   0.000     .3215526    .4133309
        5 1  |   .0233486   .0033683     6.93   0.000      .016747    .0299503
        5 2  |   .0461733   .0075597     6.11   0.000     .0313564    .0609901
------------------------------------------------------------------------------

. 
. * Remained politically active after revolution
. logit EVA223_14 gender newage newpartica if EVA_vers=="yr2005", or 

Iteration 0:   log likelihood = -279.68706  
Iteration 1:   log likelihood = -274.11032  
Iteration 2:   log likelihood = -271.64731  
Iteration 3:   log likelihood =  -271.6411  
Iteration 4:   log likelihood =  -271.6411  

Logistic regression                             Number of obs     =      1,800
                                                LR chi2(3)        =      16.09
                                                Prob > chi2       =     0.0011
Log likelihood =  -271.6411                     Pseudo R2         =     0.0288

------------------------------------------------------------------------------
   EVA223_14 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.039268   .2672072     0.15   0.881     .6278769    1.720208
      newage |   1.000756   .0078182     0.10   0.923     .9855494    1.016197
  newpartica |   3.150912   .8668498     4.17   0.000     1.837645    5.402701
       _cons |   .0269822   .0113612    -8.58   0.000     .0118214    .0615868
------------------------------------------------------------------------------

. margins, atmeans at(newpartica=(0 1))

Adjusted predictions                            Number of obs     =      1,800
Model VCE    : OIM

Expression   : Pr(EVA223_14), predict()

1._at        : gender          =    .4433333 (mean)
               newage          =    45.55444 (mean)
               newpartica      =           0

2._at        : gender          =    .4433333 (mean)
               newage          =    45.55444 (mean)
               newpartica      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0276235    .004212     6.56   0.000     .0193682    .0358788
          2  |   .0821578   .0168768     4.87   0.000     .0490799    .1152357
------------------------------------------------------------------------------

. 
. * BIOGRAPHICAL AVAILABILITY
. * Marriage for Orange and Euromaidan participants, vs. other rev supporters
. logit married  gender newage newpartica if EVA_vers=="yr2005" & partic5a~=4 & partic5a~=5, or

Iteration 0:   log likelihood = -650.85915  
Iteration 1:   log likelihood = -642.27512  
Iteration 2:   log likelihood = -642.25321  
Iteration 3:   log likelihood = -642.25321  

Logistic regression                             Number of obs     =      1,033
                                                LR chi2(3)        =      17.21
                                                Prob > chi2       =     0.0006
Log likelihood = -642.25321                     Pseudo R2         =     0.0132

------------------------------------------------------------------------------
     married | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.742811   .2398377     4.04   0.000     1.330797    2.282384
      newage |    1.00508   .0042422     1.20   0.230     .9968001    1.013429
  newpartica |    .954186   .1487994    -0.30   0.764     .7028998    1.295307
       _cons |    1.30956   .3003825     1.18   0.240     .8353719    2.052916
------------------------------------------------------------------------------

. logit married  gender newage newpartica if EVA_vers=="yr2014" & partic5a~=4 & partic5a~=5, or

Iteration 0:   log likelihood = -658.54429  
Iteration 1:   log likelihood = -649.94167  
Iteration 2:   log likelihood = -649.91882  
Iteration 3:   log likelihood = -649.91882  

Logistic regression                             Number of obs     =      1,047
                                                LR chi2(3)        =      17.25
                                                Prob > chi2       =     0.0006
Log likelihood = -649.91882                     Pseudo R2         =     0.0131

------------------------------------------------------------------------------
     married | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |    1.69851   .2306808     3.90   0.000     1.301557    2.216526
      newage |   1.004038   .0042306     0.96   0.339       .99578    1.012364
  newpartica |   1.200602   .2426478     0.90   0.366     .8079169    1.784149
       _cons |   1.342703   .2925633     1.35   0.176      .876013    2.058019
------------------------------------------------------------------------------

. 
. * Children under 6 for Orange and Euromaidan participants, vs. other rev supporters
. logit EVA264_2 gender newage newpartica if EVA_vers=="yr2005" & partic5a~=4 & partic5a~=5, or

Iteration 0:   log likelihood = -357.55422  
Iteration 1:   log likelihood = -303.69019  
Iteration 2:   log likelihood = -292.98424  
Iteration 3:   log likelihood = -292.76163  
Iteration 4:   log likelihood = -292.76157  
Iteration 5:   log likelihood = -292.76157  

Logistic regression                             Number of obs     =      1,041
                                                LR chi2(3)        =     129.59
                                                Prob > chi2       =     0.0000
Log likelihood = -292.76157                     Pseudo R2         =     0.1812

------------------------------------------------------------------------------
    EVA264_2 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   .5925995   .1296664    -2.39   0.017     .3859316     .909939
      newage |   .9174333   .0084542    -9.35   0.000     .9010121    .9341538
  newpartica |   .5180816   .1292008    -2.64   0.008     .3177773    .8446435
       _cons |   5.075308   1.826693     4.51   0.000     2.506686    10.27602
------------------------------------------------------------------------------

. logit EVA264_2 gender newage newpartica if EVA_vers=="yr2014" & partic5a~=4 & partic5a~=5, or

Iteration 0:   log likelihood = -470.03658  
Iteration 1:   log likelihood = -388.83882  
Iteration 2:   log likelihood = -376.24864  
Iteration 3:   log likelihood = -376.07763  
Iteration 4:   log likelihood = -376.07762  

Logistic regression                             Number of obs     =      1,051
                                                LR chi2(3)        =     187.92
                                                Prob > chi2       =     0.0000
Log likelihood = -376.07762                     Pseudo R2         =     0.1999

------------------------------------------------------------------------------
    EVA264_2 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   .8369659   .1551806    -0.96   0.337     .5819528    1.203726
      newage |   .9135025   .0074085   -11.16   0.000     .8990968     .928139
  newpartica |    .558868   .1589485    -2.05   0.041     .3200499    .9758899
       _cons |   7.813756   2.452558     6.55   0.000     4.223643    14.45548
------------------------------------------------------------------------------

. 
. * Health for Orange and Euromaidan participants, vs. other rev supporters
. ologit health gender newage newpartica if EVA_vers=="yr2005" & partic5a~=4 & partic5a~=5, or

Iteration 0:   log likelihood = -1020.1617  
Iteration 1:   log likelihood = -898.34471  
Iteration 2:   log likelihood = -893.49153  
Iteration 3:   log likelihood = -893.48708  
Iteration 4:   log likelihood = -893.48708  

Ordered logistic regression                     Number of obs     =      1,040
                                                LR chi2(3)        =     253.35
                                                Prob > chi2       =     0.0000
Log likelihood = -893.48708                     Pseudo R2         =     0.1242

------------------------------------------------------------------------------
      health | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.728927   .2208024     4.29   0.000     1.346074     2.22067
      newage |   .9444123   .0041489   -13.02   0.000     .9363155    .9525791
  newpartica |   1.448844   .2112674     2.54   0.011     1.088682    1.928155
-------------+----------------------------------------------------------------
       /cut1 |  -3.659629   .2542587                     -4.157967   -3.161291
       /cut2 |  -.4975264   .2159215                     -.9207248   -.0743281
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |       0.63      0.890       3
 -------------+------------------------------
       gender |       0.00      0.999       1
       newage |       0.31      0.580       1
   newpartica |       0.41      0.523       1

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. ologit health gender newage newpartica if EVA_vers=="yr2014" & partic5a~=4 & partic5a~=5, or

Iteration 0:   log likelihood = -1025.5351  
Iteration 1:   log likelihood = -906.43835  
Iteration 2:   log likelihood = -901.48899  
Iteration 3:   log likelihood = -901.48445  
Iteration 4:   log likelihood = -901.48445  

Ordered logistic regression                     Number of obs     =      1,051
                                                LR chi2(3)        =     248.10
                                                Prob > chi2       =     0.0000
Log likelihood = -901.48445                     Pseudo R2         =     0.1210

------------------------------------------------------------------------------
      health | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.723695   .2182044     4.30   0.000     1.344949    2.209098
      newage |   .9416329   .0041811   -13.54   0.000     .9334737    .9498634
  newpartica |   1.435049   .2628688     1.97   0.049      1.00218    2.054886
-------------+----------------------------------------------------------------
       /cut1 |  -4.289826   .2581238                     -4.795739   -3.783913
       /cut2 |  -1.101223   .2080421                     -1.508978   -.6934675
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |       1.72      0.633       3
 -------------+------------------------------
       gender |       1.01      0.316       1
       newage |       0.47      0.493       1
   newpartica |       0.35      0.552       1

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. 
. * APATHETIC IN ORANGE REVOLUTION
. logit apathetic gender newage  EVA251 russpeakathome  if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -517.30284  
Iteration 1:   log likelihood = -498.76083  
Iteration 2:   log likelihood = -497.86678  
Iteration 3:   log likelihood = -497.86439  
Iteration 4:   log likelihood = -497.86439  

Logistic regression                             Number of obs     =      1,732
                                                LR chi2(4)        =      38.88
                                                Prob > chi2       =     0.0000
Log likelihood = -497.86439                     Pseudo R2         =     0.0376

--------------------------------------------------------------------------------
     apathetic | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        gender |    .705732   .1251376    -1.97   0.049     .4985494    .9990137
        newage |    .975103   .0053242    -4.62   0.000     .9647234    .9855943
        EVA251 |   .8677843   .0490192    -2.51   0.012     .7768359    .9693805
russpeakathome |   1.650916   .2838592     2.92   0.004     1.178607    2.312496
         _cons |   .4327395   .1514654    -2.39   0.017     .2179179    .8593302
--------------------------------------------------------------------------------

. 
. * COUNTER-REVOLUTIONARIES IN ORANGE REVOLUTION
. *  Exercise
. logit exercise newage gender oppcounter if EVA_vers=="yr2005", or

Iteration 0:   log likelihood =  -332.0136  
Iteration 1:   log likelihood = -326.79582  
Iteration 2:   log likelihood =  -326.6599  
Iteration 3:   log likelihood = -326.65989  

Logistic regression                             Number of obs     =        605
                                                LR chi2(3)        =      10.71
                                                Prob > chi2       =     0.0134
Log likelihood = -326.65989                     Pseudo R2         =     0.0161

------------------------------------------------------------------------------
    exercise | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      newage |   .9895365   .0056109    -1.86   0.064     .9786003    1.000595
      gender |   .8412823   .1665008    -0.87   0.383     .5707919    1.239954
  oppcounter |   2.514282   .8760202     2.65   0.008     1.270107    4.977229
       _cons |   .5057406   .1461049    -2.36   0.018     .2870925    .8909102
------------------------------------------------------------------------------

. margins, atmeans at(oppcounter=(0 1))

Adjusted predictions                            Number of obs     =        605
Model VCE    : OIM

Expression   : Pr(exercise), predict()

1._at        : newage          =    46.33884 (mean)
               gender          =    .4264463 (mean)
               oppcounter      =           0

2._at        : newage          =    46.33884 (mean)
               gender          =    .4264463 (mean)
               oppcounter      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .2239393   .0176138    12.71   0.000     .1894168    .2584617
          2  |   .4204641   .0811522     5.18   0.000     .2614087    .5795194
------------------------------------------------------------------------------

. logit exercise newage gender countermob if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -870.86561  
Iteration 1:   log likelihood = -851.31004  
Iteration 2:   log likelihood = -850.65005  
Iteration 3:   log likelihood = -850.64992  
Iteration 4:   log likelihood = -850.64992  

Logistic regression                             Number of obs     =      1,747
                                                LR chi2(3)        =      40.43
                                                Prob > chi2       =     0.0000
Log likelihood = -850.64992                     Pseudo R2         =     0.0232

------------------------------------------------------------------------------
    exercise | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      newage |   .9805231   .0036506    -5.28   0.000     .9733941    .9877043
      gender |   1.102105    .134727     0.80   0.426     .8672966    1.400484
  countermob |   2.891349   .9827437     3.12   0.002     1.485199    5.628806
       _cons |   .5453924   .0991997    -3.33   0.001     .3818447    .7789891
------------------------------------------------------------------------------

. margins, atmeans at(countermob=(0 1))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

Expression   : Pr(exercise), predict()

1._at        : newage          =    45.57584 (mean)
               gender          =    .4436176 (mean)
               countermob      =           0

2._at        : newage          =    45.57584 (mean)
               gender          =    .4436176 (mean)
               countermob      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1885351   .0096357    19.57   0.000     .1696496    .2074207
          2  |   .4018329   .0804267     5.00   0.000     .2441995    .5594663
------------------------------------------------------------------------------

. 
. * Visited lawyer in last 12 mos.
. logit visitedlawyer  oppcounter if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -141.88629  
Iteration 1:   log likelihood = -140.56394  
Iteration 2:   log likelihood = -139.58497  
Iteration 3:   log likelihood = -139.58349  
Iteration 4:   log likelihood = -139.58349  

Logistic regression                             Number of obs     =        604
                                                LR chi2(1)        =       4.61
                                                Prob > chi2       =     0.0319
Log likelihood = -139.58349                     Pseudo R2         =     0.0162

-------------------------------------------------------------------------------
visitedlawyer | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
   oppcounter |   3.128906   1.503957     2.37   0.018      1.21969    8.026677
        _cons |   .0599251   .0109061   -15.47   0.000     .0419463      .08561
-------------------------------------------------------------------------------

. margins, atmeans at(oppcounter=(0 1))

Adjusted predictions                            Number of obs     =        604
Model VCE    : OIM

Expression   : Pr(visitedlawyer), predict()

1._at        : oppcounter      =           0

2._at        : oppcounter      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0565371   .0097078     5.82   0.000     .0375102     .075564
          2  |   .1578947   .0591528     2.67   0.008     .0419574    .2738321
------------------------------------------------------------------------------

. logit visitedlawyer  countermob if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -371.61179  
Iteration 1:   log likelihood = -370.85146  
Iteration 2:   log likelihood = -368.90165  
Iteration 3:   log likelihood = -368.89184  
Iteration 4:   log likelihood = -368.89183  

Logistic regression                             Number of obs     =      1,743
                                                LR chi2(1)        =       5.44
                                                Prob > chi2       =     0.0197
Log likelihood = -368.89183                     Pseudo R2         =     0.0073

-------------------------------------------------------------------------------
visitedlawyer | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
   countermob |   3.364585    1.54055     2.65   0.008     1.371482    8.254162
        _cons |   .0557276   .0060357   -26.66   0.000     .0450691    .0689066
-------------------------------------------------------------------------------

. margins, atmeans at(countermob=(0 1))

Adjusted predictions                            Number of obs     =      1,743
Model VCE    : OIM

Expression   : Pr(visitedlawyer), predict()

1._at        : countermob      =           0

2._at        : countermob      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0527859   .0054153     9.75   0.000     .0421722    .0633997
          2  |   .1578948   .0591528     2.67   0.008     .0419575    .2738322
------------------------------------------------------------------------------

. 
. * Dissatisfaction w. amenities and sanitary conditions in home
. ologit homedissat newage gender oppcounter if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -539.43457  
Iteration 1:   log likelihood = -533.81279  
Iteration 2:   log likelihood = -533.75552  
Iteration 3:   log likelihood = -533.75546  
Iteration 4:   log likelihood = -533.75546  

Ordered logistic regression                     Number of obs     =        605
                                                LR chi2(3)        =      11.36
                                                Prob > chi2       =     0.0099
Log likelihood = -533.75546                     Pseudo R2         =     0.0105

------------------------------------------------------------------------------
  homedissat | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      newage |   .9882873   .0048734    -2.39   0.017     .9787817    .9978853
      gender |   .8049694   .1363541    -1.28   0.200     .5775559    1.121927
  oppcounter |   2.238783   .9114261     1.98   0.048     1.008048    4.972134
-------------+----------------------------------------------------------------
       /cut1 |  -2.063563   .2748638                     -2.602286    -1.52484
       /cut2 |  -1.211179   .2650234                     -1.730615   -.6917424
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |       3.04      0.386       3
 -------------+------------------------------
       newage |       0.30      0.586       1
       gender |       2.28      0.131       1
   oppcounter |       0.22      0.639       1

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. margins, atmeans at(oppcounter=(0 1))

Adjusted predictions                            Number of obs     =        605
Model VCE    : OIM

1._predict   : Pr(homedissat==1), predict(pr outcome(1))
2._predict   : Pr(homedissat==2), predict(pr outcome(2))
3._predict   : Pr(homedissat==3), predict(pr outcome(3))

1._at        : newage          =    46.33884 (mean)
               gender          =    .4264463 (mean)
               oppcounter      =           0

2._at        : newage          =    46.33884 (mean)
               gender          =    .4264463 (mean)
               oppcounter      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1938649   .0165424    11.72   0.000     .1614425    .2262874
        1 2  |   .0969991     .03545     2.74   0.006     .0275184    .1664797
        2 1  |   .1667479   .0154714    10.78   0.000     .1364244    .1970714
        2 2  |   .1042288   .0300963     3.46   0.001      .045241    .1632165
        3 1  |   .6393872   .0202888    31.51   0.000     .5996218    .6791525
        3 2  |   .7987721   .0639787    12.48   0.000     .6733761    .9241682
------------------------------------------------------------------------------

. ologit homedissat newage gender countermob if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -1830.0038  
Iteration 1:   log likelihood = -1816.0407  
Iteration 2:   log likelihood = -1815.9412  
Iteration 3:   log likelihood = -1815.9412  

Ordered logistic regression                     Number of obs     =      1,747
                                                LR chi2(3)        =      28.13
                                                Prob > chi2       =     0.0000
Log likelihood = -1815.9412                     Pseudo R2         =     0.0077

------------------------------------------------------------------------------
  homedissat | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      newage |    .993046   .0026823    -2.58   0.010     .9878027    .9983171
      gender |    .797947   .0729148    -2.47   0.014     .6671031    .9544543
  countermob |   4.393393   1.752829     3.71   0.000     2.010003     9.60292
-------------+----------------------------------------------------------------
       /cut1 |  -1.280882   .1456119                     -1.566277   -.9954884
       /cut2 |   -.314245   .1423531                      -.593252    -.035238
------------------------------------------------------------------------------

. brant

Brant test of parallel regression assumption

              |       chi2     p>chi2      df
 -------------+------------------------------
          All |       1.73      0.630       3
 -------------+------------------------------
       newage |       0.85      0.356       1
       gender |       0.59      0.441       1
   countermob |       0.09      0.758       1

A significant test statistic provides evidence that the parallel
regression assumption has been violated.

. * Passed proportional odds test
. margins, atmeans at(countermob=(0 1))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

1._predict   : Pr(homedissat==1), predict(pr outcome(1))
2._predict   : Pr(homedissat==2), predict(pr outcome(2))
3._predict   : Pr(homedissat==3), predict(pr outcome(3))

1._at        : newage          =    45.57584 (mean)
               gender          =    .4436176 (mean)
               countermob      =           0

2._at        : newage          =    45.57584 (mean)
               gender          =    .4436176 (mean)
               countermob      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .2967731   .0110575    26.84   0.000     .2751008    .3184453
        1 2  |   .0876387   .0318449     2.75   0.006     .0252238    .1500535
        2 1  |    .229185   .0101543    22.57   0.000      .209283     .249087
        2 2  |   .1139851   .0323261     3.53   0.000     .0506272    .1773431
        3 1  |    .474042   .0121029    39.17   0.000     .4503207    .4977632
        3 2  |   .7983762   .0637752    12.52   0.000     .6733791    .9233732
------------------------------------------------------------------------------

. 
. * Drinking habits
. tab newdrinker oppcounter if EVA_vers=="yr2005", col chi

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

                      |   Oppose revolution
                      |  only or mobilize as
                      | counter-revolutionary
     Drinker (binary) |         0          1 |     Total
----------------------+----------------------+----------
Never or several time |       314         14 |       328 
                      |     55.38      36.84 |     54.21 
----------------------+----------------------+----------
Several times a month |       253         24 |       277 
                      |     44.62      63.16 |     45.79 
----------------------+----------------------+----------
                Total |       567         38 |       605 
                      |    100.00     100.00 |    100.00 

          Pearson chi2(1) =   4.9300   Pr = 0.026

. tab newdrinker countermob if EVA_vers=="yr2005" & partic6~=5, col chi

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

                      |       Partic in
                      | counter-revolutionary
                      |       protests
     Drinker (binary) |        no        yes |     Total
----------------------+----------------------+----------
Never or several time |       607         14 |       621 
                      |     53.15      36.84 |     52.63 
----------------------+----------------------+----------
Several times a month |       535         24 |       559 
                      |     46.85      63.16 |     47.37 
----------------------+----------------------+----------
                Total |     1,142         38 |     1,180 
                      |    100.00     100.00 |    100.00 

          Pearson chi2(1) =   3.9242   Pr = 0.048

. 
. * From Donbas
. logit donbas oppcounter if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -404.61495  
Iteration 1:   log likelihood = -404.03109  
Iteration 2:   log likelihood = -404.03064  
Iteration 3:   log likelihood = -404.03064  

Logistic regression                             Number of obs     =        605
                                                LR chi2(1)        =       1.17
                                                Prob > chi2       =     0.2797
Log likelihood = -404.03064                     Pseudo R2         =     0.0014

------------------------------------------------------------------------------
      donbas | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  oppcounter |   1.440826   .4843576     1.09   0.277     .7455312    2.784563
       _cons |   .6246418   .0539239    -5.45   0.000     .5274104    .7397984
------------------------------------------------------------------------------

. margins, atmeans at(oppcounter=(0 1))

Adjusted predictions                            Number of obs     =        605
Model VCE    : OIM

Expression   : Pr(donbas), predict()

1._at        : oppcounter      =           0

2._at        : oppcounter      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3844797   .0204299    18.82   0.000     .3444378    .4245216
          2  |   .4736842   .0809983     5.85   0.000     .3149305    .6324379
------------------------------------------------------------------------------

. logit donbas countermob if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -760.56439  
Iteration 1:   log likelihood = -752.90901  
Iteration 2:   log likelihood = -749.84918  
Iteration 3:   log likelihood = -749.82329  
Iteration 4:   log likelihood = -749.82329  

Logistic regression                             Number of obs     =      1,747
                                                LR chi2(1)        =      21.48
                                                Prob > chi2       =     0.0000
Log likelihood = -749.82329                     Pseudo R2         =     0.0141

------------------------------------------------------------------------------
      donbas | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  countermob |   5.084825   1.687483     4.90   0.000     2.653327    9.744537
       _cons |   .1769972   .0119781   -25.59   0.000      .155011     .202102
------------------------------------------------------------------------------

. margins, atmeans at(countermob=(0 1))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

Expression   : Pr(donbas), predict()

1._at        : countermob      =           0

2._at        : countermob      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .1503803   .0086464    17.39   0.000     .1334337     .167327
          2  |   .4736842   .0809983     5.85   0.000     .3149305    .6324379
------------------------------------------------------------------------------

. 
. * From Donbas--KIIS sample
. clear

. use mohyla.orangerev.dta

. logit donbas age gender i.demopartvote , or

Iteration 0:   log likelihood = -869.07367  
Iteration 1:   log likelihood = -671.34165  
Iteration 2:   log likelihood = -639.81841  
Iteration 3:   log likelihood = -627.54476  
Iteration 4:   log likelihood = -627.38565  
Iteration 5:   log likelihood = -627.38508  
Iteration 6:   log likelihood = -627.38508  

Logistic regression                             Number of obs     =      1,907
                                                LR chi2(6)        =     483.38
                                                Prob > chi2       =     0.0000
Log likelihood = -627.38508                     Pseudo R2         =     0.2781

---------------------------------------------------------------------------------------
               donbas | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
                  age |    1.00379   .0038856     0.98   0.328     .9962032    1.011434
               gender |   1.144877   .1647702     0.94   0.347     .8634839    1.517971
                      |
         demopartvote |
Orange vote, no demo  |    .855573    .540694    -0.25   0.805      .247928     2.95249
    No vote, no demo  |   4.183119   2.371996     2.52   0.012     1.376686    12.71059
  Blue vote, no demo  |    32.2363   16.47335     6.80   0.000     11.84038    87.76572
     Blue demo, vote  |   173.7334   97.42007     9.20   0.000     57.88639    521.4228
                      |
                _cons |   .0118303   .0063159    -8.31   0.000     .0041549    .0336845
---------------------------------------------------------------------------------------

. margins, atmeans at(demopartvote=(4 5))

Adjusted predictions                            Number of obs     =      1,907
Model VCE    : OIM

Expression   : Pr(donbas), predict()

1._at        : age             =    47.23755 (mean)
               gender          =     .408495 (mean)
               demopartvote    =           4

2._at        : age             =    47.23755 (mean)
               gender          =     .408495 (mean)
               demopartvote    =           5

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .3251862   .0174584    18.63   0.000     .2909683    .3594041
          2  |   .7219971   .0494535    14.60   0.000       .62507    .8189242
------------------------------------------------------------------------------

. 
. * REVOLUTIONARY HELPERS IN ORANGE REVOLUTION
. clear

. use monitoring20052014engmerged.dta

. logit EVA250_3  gender newage ib(3).partic5a if EVA_vers=="yr2005", or

Iteration 0:   log likelihood = -885.99367  
Iteration 1:   log likelihood = -860.20204  
Iteration 2:   log likelihood = -859.45326  
Iteration 3:   log likelihood =  -859.4529  
Iteration 4:   log likelihood =  -859.4529  

Logistic regression                             Number of obs     =      1,747
                                                LR chi2(6)        =      53.08
                                                Prob > chi2       =     0.0000
Log likelihood =  -859.4529                     Pseudo R2         =     0.0300

------------------------------------------------------------------------------
    EVA250_3 | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   1.469671   .1781076     3.18   0.001     1.158949    1.863701
      newage |   .9846428   .0037078    -4.11   0.000     .9774024    .9919369
             |
    partic5a |
Part in rev  |   1.071123    .184725     0.40   0.690     .7639091    1.501885
    Aid rev  |   2.397973   .6915162     3.03   0.002     1.362632    4.219974
  Apathetic  |    .521793   .1345838    -2.52   0.012     .3147397    .8650575
 Oppose rev  |   .7656081   .1113307    -1.84   0.066     .5757439    1.018084
             |
       _cons |   .4651524   .0978616    -3.64   0.000     .3079742    .7025484
------------------------------------------------------------------------------

. margins, atmeans at(partic5a=(1 2 3 4 5))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

Expression   : Pr(EVA250_3), predict()

1._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               partic5a        =           1

2._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               partic5a        =           2

3._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               partic5a        =           3

4._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               partic5a        =           4

5._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               partic5a        =           5

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .2259682   .0249623     9.05   0.000     .1770431    .2748934
          2  |   .3952487    .064946     6.09   0.000     .2679568    .5225405
          3  |   .2141775   .0163596    13.09   0.000     .1821133    .2462417
          4  |   .1245086   .0260133     4.79   0.000     .0735236    .1754937
          5  |    .172643   .0154655    11.16   0.000     .1423311    .2029548
------------------------------------------------------------------------------

. ttest newage if EVA_vers=="yr2005", by(particoraid)

Two-sample t test with equal variances
------------------------------------------------------------------------------
   Group |     Obs        Mean    Std. Err.   Std. Dev.   [95% Conf. Interval]
---------+--------------------------------------------------------------------
      no |     279    39.62724    .9122651    15.23783    37.83142    41.42306
     yes |      58    47.31034    2.122704    16.16603     43.0597    51.56099
---------+--------------------------------------------------------------------
combined |     337    40.94955    .8524382    15.64869    39.27277    42.62634
---------+--------------------------------------------------------------------
    diff |           -7.683105    2.222345               -12.05461   -3.311595
------------------------------------------------------------------------------
    diff = mean(no) - mean(yes)                                   t =  -3.4572
Ho: diff = 0                                     degrees of freedom =      335

    Ha: diff < 0                 Ha: diff != 0                 Ha: diff > 0
 Pr(T < t) = 0.0003         Pr(|T| > |t|) = 0.0006          Pr(T > t) = 0.9997

. 
. * EGYPTIAN REVOLUTION
. clear

. use fullarabbarom2.dta

. * Egypt--social structural basis for support or opposition to revolution
. logit opposerev gender newage  edlvl religscale christian farmer if country==2, or

Iteration 0:   log likelihood = -487.94247  
Iteration 1:   log likelihood = -466.60471  
Iteration 2:   log likelihood =  -465.6735  
Iteration 3:   log likelihood = -465.67162  
Iteration 4:   log likelihood = -465.67162  

Logistic regression                             Number of obs     =      1,125
                                                LR chi2(6)        =      44.54
                                                Prob > chi2       =     0.0000
Log likelihood = -465.67162                     Pseudo R2         =     0.0456

------------------------------------------------------------------------------
   opposerev | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      gender |   .5973954    .111225    -2.77   0.006     .4147462    .8604811
      newage |   .9914594   .0065648    -1.30   0.195     .9786758     1.00441
       edlvl |   .8822322   .0438709    -2.52   0.012     .8003041    .9725474
  religscale |   .9229361   .0290818    -2.55   0.011     .8676612    .9817323
   christian |   2.139346   .6786935     2.40   0.017     1.148796    3.983999
      farmer |     2.0106   .5969767     2.35   0.019     1.123548     3.59799
       _cons |   .8476021   .3044125    -0.46   0.645     .4192632    1.713552
------------------------------------------------------------------------------

. 
. * Those who aided revolutionaries had friends who participated
. tab frpart egpartic5 if country==2 & egpartic5~=1 & egpartic5~=4 & egpartic5~=5, col chi

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Did |
friends/ac |
quaintance |
         s |
participat |        Egypt:
      e in | Part/Aid/Support/Apat
protests(q |       h/Oppose
 806/905)? |       Aid    Support |     Total
-----------+----------------------+----------
        no |         5        637 |       642 
           |     17.86      76.38 |     74.48 
-----------+----------------------+----------
       yes |        23        197 |       220 
           |     82.14      23.62 |     25.52 
-----------+----------------------+----------
     Total |        28        834 |       862 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =  48.8099   Pr = 0.000

. 
. 
. * =============================================================
. * DATA FOR FIGURE 7.3: GENDER DIFFERENCES, CONTROLLING FOR AGE
. * =============================================================
. * Ukrainian revolutions
. clear

. use monitoring20052014engmerged.dta

. * Orange Revolution
. * By gender
. mlogit partic5a gender newage if EVA_vers=="yr2005", rrr b(3)

Iteration 0:   log likelihood = -2367.5224  
Iteration 1:   log likelihood = -2322.5232  
Iteration 2:   log likelihood = -2321.7178  
Iteration 3:   log likelihood = -2321.7173  
Iteration 4:   log likelihood = -2321.7173  

Multinomial logistic regression                 Number of obs     =      1,747
                                                LR chi2(8)        =      91.61
                                                Prob > chi2       =     0.0000
Log likelihood = -2321.7173                     Pseudo R2         =     0.0193

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.512605   .2217658     2.82   0.005     1.134826    2.016145
      newage |   .9681941   .0044208    -7.08   0.000     .9595681    .9768976
       _cons |   1.453275   .3246018     1.67   0.094     .9380463    2.251496
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |    1.34187   .3698615     1.07   0.286     .7817947    2.303183
      newage |   .9962151   .0082382    -0.46   0.647     .9801987    1.012493
       _cons |    .093292   .0418648    -5.29   0.000      .038714    .2248128
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |     .77328   .1438354    -1.38   0.167      .537041    1.113438
      newage |   .9679722   .0054693    -5.76   0.000     .9573118    .9787514
       _cons |   1.105985   .2950158     0.38   0.706      .655686    1.865533
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .9842088   .1131177    -0.14   0.890     .7856995    1.232872
      newage |   .9918905   .0033712    -2.40   0.017      .985305    .9985201
       _cons |   1.377177   .2504611     1.76   0.078     .9642411    1.966954
------------------------------------------------------------------------------

. margins, atmeans at(gender=(0 1))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =           0
               newage          =    45.57584 (mean)

2._at        : gender          =           1
               newage          =    45.57584 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1274939   .0109023    11.69   0.000     .1061259     .148862
        1 2  |   .1839957    .014186    12.97   0.000     .1561916    .2117998
        2 1  |   .0300402   .0055505     5.41   0.000     .0191614     .040919
        2 2  |   .0384597   .0070038     5.49   0.000     .0247324     .052187
        3 1  |   .3827512   .0158964    24.08   0.000     .3515949    .4139076
        3 2  |   .3651819   .0176061    20.74   0.000     .3306745    .3996892
        4 1  |   .0960186   .0096571     9.94   0.000     .0770911    .1149461
        4 2  |    .070841   .0092487     7.66   0.000     .0527139    .0889681
        5 1  |   .3636961   .0156603    23.22   0.000     .3330024    .3943897
        5 2  |   .3415218   .0172634    19.78   0.000     .3076862    .3753574
------------------------------------------------------------------------------

. * Average probability for all
. tab partic5a if EVA_vers=="yr2005" & e(sample)

Part/Aid/Su |
pport/Apath |
etic/Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        279       15.97       15.97
    Aid rev |         58        3.32       19.29
Support rev |        651       37.26       56.55
  Apathetic |        154        8.82       65.37
 Oppose rev |        605       34.63      100.00
------------+-----------------------------------
      Total |      1,747      100.00

. * Euromaidan
. * By gender
. mlogit partic5a gender newage if EVA_vers=="yr2014", rrr b(3)

Iteration 0:   log likelihood = -2440.8253  
Iteration 1:   log likelihood = -2423.6789  
Iteration 2:   log likelihood = -2423.3628  
Iteration 3:   log likelihood = -2423.3626  

Multinomial logistic regression                 Number of obs     =      1,752
                                                LR chi2(8)        =      34.93
                                                Prob > chi2       =     0.0000
Log likelihood = -2423.3626                     Pseudo R2         =     0.0072

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.639532   .3067083     2.64   0.008      1.13628    2.365673
      newage |   .9832662   .0057941    -2.86   0.004     .9719754    .9946883
       _cons |   .3195324   .0944488    -3.86   0.000     .1790247    .5703176
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.003189   .1894936     0.02   0.987     .6927841    1.452671
      newage |   .9914343   .0058389    -1.46   0.144      .980056    1.002945
       _cons |   .2744691   .0821617    -4.32   0.000      .152647     .493513
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .6148711   .0975284    -3.07   0.002     .4505779    .8390702
      newage |   .9951647   .0047234    -1.02   0.307     .9859499    1.004465
       _cons |   .4777718   .1158272    -3.05   0.002     .2970722    .7683854
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .8609188   .1001948    -1.29   0.198     .6853277    1.081499
      newage |   1.000196   .0035717     0.05   0.956     .9932199    1.007221
       _cons |   .7606943   .1424428    -1.46   0.144     .5270108    1.097996
------------------------------------------------------------------------------

. margins, atmeans at(gender=(0 1))

Adjusted predictions                            Number of obs     =      1,752
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =           0
               newage          =    45.76998 (mean)

2._at        : gender          =           1
               newage          =    45.76998 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0594426   .0076122     7.81   0.000      .044523    .0743621
        1 2  |   .1041331   .0110446     9.43   0.000     .0824861    .1257801
        2 1  |   .0745621   .0084553     8.82   0.000     .0579901    .0911342
        2 2  |    .079923   .0097535     8.19   0.000     .0608065    .0990395
        3 1  |   .4027402   .0157939    25.50   0.000     .3717848    .4336956
        3 2  |   .4303245   .0178263    24.14   0.000     .3953857    .4652633
        4 1  |   .1541335   .0116236    13.26   0.000     .1313516    .1769154
        4 2  |   .1012633   .0108424     9.34   0.000     .0800126    .1225141
        5 1  |   .3091215   .0148821    20.77   0.000     .2799532    .3382899
        5 2  |   .2843561   .0162365    17.51   0.000      .252533    .3161791
------------------------------------------------------------------------------

. * Average probability for all
. tab partic5a if EVA_vers=="yr2014" & e(sample)

Part/Aid/Su |
pport/Apath |
etic/Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        143        8.16        8.16
    Aid rev |        135        7.71       15.87
Support rev |        725       41.38       57.25
  Apathetic |        228       13.01       70.26
 Oppose rev |        521       29.74      100.00
------------+-----------------------------------
      Total |      1,752      100.00

. * Egyptian and Tunisian revolutions
. clear

. use fullarabbarom2.dta

. * Egyptian Revolution
. * By gender
. mlogit egpartic5 gender newage if country==2 [pw=WT], rrr b(3)

Iteration 0:   log pseudolikelihood = -1209.7412  
Iteration 1:   log pseudolikelihood = -1188.8705  
Iteration 2:   log pseudolikelihood = -1187.7773  
Iteration 3:   log pseudolikelihood = -1187.7736  
Iteration 4:   log pseudolikelihood = -1187.7736  

Multinomial logistic regression                 Number of obs     =      1,211
                                                Wald chi2(8)      =      39.63
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1187.7736               Pseudo R2         =     0.0182

------------------------------------------------------------------------------
             |               Robust
   egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Participate  |
      gender |   3.320797   .8659358     4.60   0.000     1.991965    5.536086
      newage |    .982873   .0077134    -2.20   0.028     .9678707    .9981078
       _cons |   .0951448   .0347741    -6.44   0.000     .0464818    .1947543
-------------+----------------------------------------------------------------
Aid          |
      gender |   1.257613   .4998654     0.58   0.564     .5770571    2.740788
      newage |   1.007537   .0121605     0.62   0.534     .9839826    1.031655
       _cons |   .0218605   .0117059    -7.14   0.000     .0076535    .0624399
-------------+----------------------------------------------------------------
Support      |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .9890779   .2360932    -0.05   0.963     .6195102    1.579111
      newage |   1.012606   .0083682     1.52   0.130     .9963364     1.02914
       _cons |   .0578094   .0216122    -7.62   0.000     .0277827     .120288
-------------+----------------------------------------------------------------
Oppose       |
      gender |   .6592923   .1137342    -2.41   0.016     .4701512    .9245245
      newage |   .9935078   .0063916    -1.01   0.311     .9810591    1.006114
       _cons |   .3317587   .0876348    -4.18   0.000     .1976858    .5567613
------------------------------------------------------------------------------

. margins, atmeans at(gender=(0 1))

Adjusted predictions                            Number of obs     =      1,211
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =           0
               newage          =    37.88005 (mean)

2._at        : gender          =           1
               newage          =    37.88005 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0345665   .0073429     4.71   0.000     .0201747    .0489584
        1 2  |   .1122065   .0131613     8.53   0.000     .0864109    .1380021
        2 1  |   .0203076   .0056071     3.62   0.000     .0093178    .0312973
        2 2  |   .0249646   .0068244     3.66   0.000      .011589    .0383402
        3 1  |   .6989884   .0189377    36.91   0.000     .6618712    .7361055
        3 2  |   .6832661   .0195569    34.94   0.000     .6449352    .7215969
        4 1  |   .0649453   .0101199     6.42   0.000     .0451108    .0847799
        4 2  |   .0627911   .0101369     6.19   0.000     .0429231    .0826592
        5 1  |   .1811922   .0160575    11.28   0.000     .1497201    .2126644
        5 2  |   .1167717   .0133972     8.72   0.000     .0905136    .1430297
------------------------------------------------------------------------------

. * Average probability for all
. tab egpartic5 if country==2 & e(sample)

     Egypt: |
Part/Aid/Su |
pport/Apath |
    /Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Participate |         90        7.43        7.43
        Aid |         28        2.31        9.74
    Support |        834       68.87       78.61
  Apathetic |         82        6.77       85.38
     Oppose |        177       14.62      100.00
------------+-----------------------------------
      Total |      1,211      100.00

. * Tunisian Revolution
. * By gender
. mlogit tpartic4 gender newage if country==10 [pw=WT], rrr b(2)

Iteration 0:   log pseudolikelihood = -1029.9264  
Iteration 1:   log pseudolikelihood = -967.59851  
Iteration 2:   log pseudolikelihood = -961.90516  
Iteration 3:   log pseudolikelihood =  -961.8796  
Iteration 4:   log pseudolikelihood =  -961.8796  

Multinomial logistic regression                 Number of obs     =      1,154
                                                Wald chi2(6)      =     109.34
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -961.8796               Pseudo R2         =     0.0661

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
            gender |   5.467714   1.123444     8.27   0.000     3.655195    8.179017
            newage |   .9597035   .0064786    -6.09   0.000     .9470892    .9724858
             _cons |   .3283564   .0956102    -3.82   0.000     .1855643    .5810274
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
            gender |   .9224881   .1777737    -0.42   0.675     .6323024     1.34585
            newage |   .9941307   .0061716    -0.95   0.343     .9821078    1.006301
             _cons |   .2122113   .0552084    -5.96   0.000     .1274447     .353358
-------------------+----------------------------------------------------------------
Oppose             |
            gender |   2.398876   .8384881     2.50   0.012     1.209161    4.759172
            newage |   .9664263   .0142134    -2.32   0.020     .9389662    .9946895
             _cons |   .1083736   .0556823    -4.32   0.000     .0395892    .2966676
------------------------------------------------------------------------------------

. margins, atmeans at(gender=(0 1))

Adjusted predictions                            Number of obs     =      1,154
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))

1._at        : gender          =           0
               newage          =    39.67621 (mean)

2._at        : gender          =           1
               newage          =    39.67621 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0509543   .0086524     5.89   0.000     .0339959    .0679128
        1 2  |   .2231778   .0184617    12.09   0.000     .1869936    .2593621
        2 1  |   .7935388   .0171722    46.21   0.000     .7598819    .8271956
        2 2  |   .6356711   .0209105    30.40   0.000     .5946873    .6766548
        3 1  |   .1333228   .0145049     9.19   0.000     .1048937    .1617518
        3 2  |   .0985211   .0125776     7.83   0.000     .0738695    .1231728
        4 1  |   .0221842    .006606     3.36   0.001     .0092366    .0351318
        4 2  |     .04263   .0083892     5.08   0.000     .0261875    .0590724
------------------------------------------------------------------------------

. * Average probability for all
. tab tpartic4 if country==10 & e(sample)

          Tunisia: |
Part/Supp/Apath,In |
        act/Oppose |      Freq.     Percent        Cum.
-------------------+-----------------------------------
       Participate |        171       14.82       14.82
           Support |        812       70.36       85.18
Apathetic/inactive |        132       11.44       96.62
            Oppose |         39        3.38      100.00
-------------------+-----------------------------------
             Total |      1,154      100.00

. * Participation by Egyptian housewives
. tab housewife egrevpart if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

      housewife dummy |    Participated in
     (q1005, excl ret |  Egyptian rev (0/1)
      student unempl) |         0          1 |     Total
----------------------+----------------------+----------
employed, unempl, stu |       669         78 |       747 
                      |     59.68      86.67 |     61.68 
----------------------+----------------------+----------
            housewife |       452         12 |       464 
                      |     40.32      13.33 |     38.32 
----------------------+----------------------+----------
                Total |     1,121         90 |     1,211 
                      |    100.00     100.00 |    100.00 


. 
. * =============================================================
. * DATA FOR FIGURE 7.4: AGE DIFFERENCES, CONTROLLING FOR GENDER
. * =============================================================
. * Ukrainian revolutions
. clear

. use monitoring20052014engmerged.dta

. * Orange Revolution
. * By age
. mlogit partic5a gender agecat if EVA_vers=="yr2005", rrr b(3)

Iteration 0:   log likelihood = -2367.5224  
Iteration 1:   log likelihood = -2325.1064  
Iteration 2:   log likelihood = -2324.3784  
Iteration 3:   log likelihood =  -2324.378  
Iteration 4:   log likelihood =  -2324.378  

Multinomial logistic regression                 Number of obs     =      1,747
                                                LR chi2(8)        =      86.29
                                                Prob > chi2       =     0.0000
Log likelihood =  -2324.378                     Pseudo R2         =     0.0182

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.535507   .2246275     2.93   0.003     1.152738    2.045375
      agecat |   .7358633   .0336896    -6.70   0.000     .6727088    .8049469
       _cons |   .9619637   .1744794    -0.21   0.831     .6741696    1.372613
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.344348   .3701575     1.07   0.283     .7836803    2.306134
      agecat |   .9635541    .080748    -0.44   0.658      .817605    1.135556
       _cons |   .0890945   .0329655    -6.54   0.000     .0431421    .1839928
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |    .783278   .1455496    -1.31   0.189     .5441827    1.127424
      agecat |   .7244536   .0412226    -5.66   0.000     .6480011    .8099261
       _cons |   .7598657   .1619991    -1.29   0.198     .5003403    1.154006
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .9910442   .1137351    -0.08   0.938     .7914193    1.241022
      agecat |   .9340085   .0321574    -1.98   0.047     .8730606    .9992111
       _cons |   1.196861   .1790272     1.20   0.230     .8927308    1.604601
------------------------------------------------------------------------------

. margins, atmeans at(agecat=(1 2 3 4 5 6))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4436176 (mean)
               agecat          =           1

2._at        : gender          =    .4436176 (mean)
               agecat          =           2

3._at        : gender          =    .4436176 (mean)
               agecat          =           3

4._at        : gender          =    .4436176 (mean)
               agecat          =           4

5._at        : gender          =    .4436176 (mean)
               agecat          =           5

6._at        : gender          =    .4436176 (mean)
               agecat          =           6

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .2404085   .0197597    12.17   0.000     .2016802    .2791369
        1 2  |   .2017998   .0128356    15.72   0.000     .1766425    .2269571
        1 3  |   .1664703   .0093418    17.82   0.000     .1481607    .1847798
        1 4  |   .1351827   .0092102    14.68   0.000     .1171311    .1532344
        1 5  |   .1082671   .0103049    10.51   0.000     .0880698    .1284645
        1 6  |   .0856855   .0111171     7.71   0.000     .0638963    .1074746
        2 1  |   .0274857   .0067759     4.06   0.000     .0142052    .0407662
        2 2  |   .0302104   .0055432     5.45   0.000      .019346    .0410748
        2 3  |   .0326326   .0045462     7.18   0.000     .0237223    .0415429
        2 4  |   .0346988   .0046158     7.52   0.000     .0256519    .0437457
        2 5  |   .0363889   .0061298     5.94   0.000     .0243747    .0484031
        2 6  |   .0377102   .0085498     4.41   0.000     .0209529    .0544675
        3 1  |   .2807821   .0188417    14.90   0.000     .2438531    .3177112
        3 2  |   .3202899   .0150853    21.23   0.000     .2907231    .3498566
        3 3  |   .3590558   .0122665    29.27   0.000     .3350139    .3830976
        3 4  |   .3962318   .0124191    31.90   0.000     .3718907    .4205729
        3 5  |   .4312485   .0162093    26.60   0.000     .3994789    .4630182
        3 6  |   .4638108   .0221892    20.90   0.000     .4203208    .5073008
        4 1  |   .1386935   .0160972     8.62   0.000     .1071436    .1702434
        4 2  |   .1146147   .0100755    11.38   0.000     .0948672    .1343622
        4 3  |   .0930828   .0072346    12.87   0.000     .0789032    .1072625
        4 4  |   .0744162   .0070771    10.52   0.000     .0605453    .0882871
        4 5  |   .0586755   .0077166     7.60   0.000     .0435512    .0737997
        4 6  |   .0457173   .0080786     5.66   0.000     .0298836     .061551
        5 1  |   .3126301   .0198142    15.78   0.000      .273795    .3514653
        5 2  |   .3330852    .015177    21.95   0.000     .3033388    .3628316
        5 3  |   .3487586   .0120914    28.84   0.000     .3250599    .3724573
        5 4  |   .3594704   .0122084    29.44   0.000     .3355425    .3833984
        5 5  |     .36542   .0157536    23.20   0.000     .3345434    .3962965
        5 6  |   .3670763   .0212883    17.24   0.000      .325352    .4088006
------------------------------------------------------------------------------

. * Average probability for all
. tab partic5a  if EVA_vers=="yr2005" & e(sample)

Part/Aid/Su |
pport/Apath |
etic/Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        279       15.97       15.97
    Aid rev |         58        3.32       19.29
Support rev |        651       37.26       56.55
  Apathetic |        154        8.82       65.37
 Oppose rev |        605       34.63      100.00
------------+-----------------------------------
      Total |      1,747      100.00

. * Euromaidan
. * By age
. mlogit partic5a gender agecat if EVA_vers=="yr2014", rrr b(3)

Iteration 0:   log likelihood = -2440.8253  
Iteration 1:   log likelihood = -2424.2114  
Iteration 2:   log likelihood = -2423.9222  
Iteration 3:   log likelihood =  -2423.922  

Multinomial logistic regression                 Number of obs     =      1,752
                                                LR chi2(8)        =      33.81
                                                Prob > chi2       =     0.0000
Log likelihood =  -2423.922                     Pseudo R2         =     0.0069

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.645655   .3077254     2.66   0.008     1.140698    2.374145
      agecat |   .8503679   .0506756    -2.72   0.007     .7566265    .9557233
       _cons |    .260371   .0635623    -5.51   0.000     .1613599    .4201357
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.007087   .1901749     0.04   0.970     .6955513     1.45816
      agecat |   .9268729   .0555405    -1.27   0.205     .8241648     1.04238
       _cons |   .2413211   .0596947    -5.75   0.000     .1486061    .3918806
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .6119056   .0970706    -3.10   0.002     .4483868     .835057
      agecat |   .9355291   .0454085    -1.37   0.170     .8506323    1.028899
       _cons |   .4833632   .0957515    -3.67   0.000     .3278351    .7126753
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .8593463   .1000031    -1.30   0.193     .6840895    1.079502
      agecat |   .9959331   .0364764    -0.11   0.911     .9269465    1.070054
       _cons |   .7794725    .120941    -1.61   0.108      .575083    1.056504
------------------------------------------------------------------------------

. margins, atmeans at(agecat=(1 2 3 4 5 6))

Adjusted predictions                            Number of obs     =      1,752
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4452055 (mean)
               agecat          =           1

2._at        : gender          =    .4452055 (mean)
               agecat          =           2

3._at        : gender          =    .4452055 (mean)
               agecat          =           3

4._at        : gender          =    .4452055 (mean)
               agecat          =           4

5._at        : gender          =    .4452055 (mean)
               agecat          =           5

6._at        : gender          =    .4452055 (mean)
               agecat          =           6

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1067212   .0147232     7.25   0.000     .0778644    .1355781
        1 2  |   .0937999   .0096475     9.72   0.000     .0748912    .1127086
        1 3  |   .0822335   .0069214    11.88   0.000     .0686678    .0957992
        1 4  |   .0719243   .0068182    10.55   0.000     .0585608    .0852878
        1 5  |   .0627718   .0080988     7.75   0.000     .0468985     .078645
        1 6  |   .0546753   .0095257     5.74   0.000     .0360054    .0733453
        2 1  |   .0866397   .0129114     6.71   0.000     .0613338    .1119456
        2 2  |   .0830007   .0090986     9.12   0.000     .0651679    .1008336
        2 3  |   .0793125    .006743    11.76   0.000     .0660964    .0925286
        2 4  |   .0756104   .0067471    11.21   0.000     .0623863    .0888346
        2 5  |   .0719257   .0086184     8.35   0.000     .0550338    .0888175
        2 6  |   .0682848   .0111279     6.14   0.000     .0464745    .0900951
        3 1  |   .3861323   .0217448    17.76   0.000     .3435133    .4287513
        3 2  |   .3990991   .0161892    24.65   0.000     .3673689    .4308294
        3 3  |   .4114531   .0124251    33.11   0.000     .3871003    .4358059
        3 4  |   .4231948   .0124867    33.89   0.000     .3987213    .4476683
        3 5  |   .4343324   .0165063    26.31   0.000     .4019806    .4666842
        3 6  |   .4448794    .022569    19.71   0.000     .4006451    .4891138
        4 1  |    .140313   .0158097     8.88   0.000     .1093266    .1712993
        4 2  |    .135675    .011317    11.99   0.000      .113494     .157856
        4 3  |   .1308569   .0084981    15.40   0.000     .1142009    .1475129
        4 4  |    .125914    .008503    14.81   0.000     .1092485    .1425795
        4 5  |   .1208963   .0108759    11.12   0.000       .09958    .1422126
        4 6  |   .1158485   .0141574     8.18   0.000     .0881005    .1435965
        5 1  |   .2801938   .0199899    14.02   0.000     .2410143    .3193732
        5 2  |   .2884253   .0149732    19.26   0.000     .2590783    .3177722
        5 3  |    .296144   .0115292    25.69   0.000     .2735471     .318741
        5 4  |   .3033564   .0115965    26.16   0.000     .2806277    .3260852
        5 5  |   .3100739   .0153983    20.14   0.000     .2798939    .3402539
        5 6  |   .3163119   .0211786    14.94   0.000     .2748027    .3578212
------------------------------------------------------------------------------

. tab partic5a  if EVA_vers=="yr2014" & e(sample)

Part/Aid/Su |
pport/Apath |
etic/Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        143        8.16        8.16
    Aid rev |        135        7.71       15.87
Support rev |        725       41.38       57.25
  Apathetic |        228       13.01       70.26
 Oppose rev |        521       29.74      100.00
------------+-----------------------------------
      Total |      1,752      100.00

. * Egyptian and Tunisian revolutions
. clear

. use fullarabbarom2.dta

. * Egyptian Revolution
. * By age
. mlogit egpartic5 gender newagelvl if country==2 [pw=WT], rrr b(3)

Iteration 0:   log pseudolikelihood = -1209.7412  
Iteration 1:   log pseudolikelihood = -1189.1128  
Iteration 2:   log pseudolikelihood = -1188.0591  
Iteration 3:   log pseudolikelihood = -1188.0555  
Iteration 4:   log pseudolikelihood = -1188.0555  

Multinomial logistic regression                 Number of obs     =      1,211
                                                Wald chi2(8)      =      38.75
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1188.0555               Pseudo R2         =     0.0179

------------------------------------------------------------------------------
             |               Robust
   egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Participate  |
      gender |   3.328509   .8681457     4.61   0.000     1.996358    5.549593
   newagelvl |   .8519032   .0659233    -2.07   0.038      .732017    .9914237
       _cons |   .0764272   .0229705    -8.56   0.000     .0424049    .1377462
-------------+----------------------------------------------------------------
Aid          |
      gender |   1.258264    .501431     0.58   0.564     .5761814    2.747794
   newagelvl |   1.066908   .1366594     0.51   0.613     .8300369    1.371377
       _cons |   .0244231   .0107152    -8.46   0.000     .0103359    .0577101
-------------+----------------------------------------------------------------
Support      |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .9879688   .2356864    -0.05   0.960     .6189899    1.576895
   newagelvl |   1.131267   .0963583     1.45   0.148     .9573305    1.336805
       _cons |   .0666599   .0202493    -8.92   0.000     .0367532    .1209021
-------------+----------------------------------------------------------------
Oppose       |
      gender |   .6605158    .113997    -2.40   0.016     .4709515    .9263822
   newagelvl |   .9309262   .0598793    -1.11   0.266     .8206614    1.056006
       _cons |   .3140264   .0633734    -5.74   0.000     .2114394    .4663871
------------------------------------------------------------------------------

. margins, atmeans at(newagelvl=(1 2 3 4 5 6))

Adjusted predictions                            Number of obs     =      1,211
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =    .5082399 (mean)
               newagelvl       =           1

2._at        : gender          =    .5082399 (mean)
               newagelvl       =           2

3._at        : gender          =    .5082399 (mean)
               newagelvl       =           3

4._at        : gender          =    .5082399 (mean)
               newagelvl       =           4

5._at        : gender          =    .5082399 (mean)
               newagelvl       =           5

6._at        : gender          =    .5082399 (mean)
               newagelvl       =           6

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0821151   .0137244     5.98   0.000     .0552158    .1090144
        1 2  |   .0710396   .0090928     7.81   0.000      .053218    .0888613
        1 3  |   .0612486   .0073803     8.30   0.000     .0467836    .0757137
        1 4  |   .0526314   .0079795     6.60   0.000     .0369918    .0682709
        1 5  |   .0450785   .0092719     4.86   0.000     .0269059    .0632511
        1 6  |   .0384846   .0103913     3.70   0.000      .018118    .0588512
        2 1  |   .0200444   .0064399     3.11   0.002     .0074224    .0326663
        2 2  |   .0217174    .005042     4.31   0.000     .0118352    .0315995
        2 3  |   .0234498   .0044414     5.28   0.000     .0147449    .0321547
        2 4  |   .0252362   .0055745     4.53   0.000     .0143103    .0361621
        2 5  |   .0270699   .0082257     3.29   0.001     .0109478     .043192
        2 6  |   .0289428   .0117987     2.45   0.014     .0058177    .0520679
        3 1  |   .6844735   .0231646    29.55   0.000     .6390718    .7298753
        3 2  |    .695095   .0161232    43.11   0.000     .6634941    .7266958
        3 3  |   .7034766   .0137164    51.29   0.000      .676593    .7303602
        3 4  |   .7095901   .0172668    41.10   0.000     .6757478    .7434324
        3 5  |   .7134154   .0242746    29.39   0.000     .6658382    .7609927
        3 6  |   .7149402   .0329719    21.68   0.000     .6503164     .779564
        4 1  |   .0512996   .0103839     4.94   0.000     .0309475    .0716517
        4 2  |   .0589341   .0083251     7.08   0.000     .0426173    .0752509
        4 3  |   .0674741   .0073746     9.15   0.000     .0530202     .081928
        4 4  |   .0769946   .0098303     7.83   0.000     .0577276    .0962616
        4 5  |    .087571   .0157264     5.57   0.000     .0567479    .1183941
        4 6  |   .0992778   .0240898     4.12   0.000     .0520627     .146493
        5 1  |   .1620674   .0188666     8.59   0.000     .1250895    .1990453
        5 2  |   .1532139   .0125563    12.20   0.000      .128604    .1778239
        5 3  |   .1443508   .0106529    13.55   0.000     .1234714    .1652301
        5 4  |   .1355477   .0136277     9.95   0.000     .1088379    .1622576
        5 5  |   .1268652    .018424     6.89   0.000     .0907548    .1629756
        5 6  |   .1183545   .0233131     5.08   0.000     .0726617    .1640474
------------------------------------------------------------------------------

. * Average probability for all
. tab egpartic5 if country==2 & e(sample)

     Egypt: |
Part/Aid/Su |
pport/Apath |
    /Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Participate |         90        7.43        7.43
        Aid |         28        2.31        9.74
    Support |        834       68.87       78.61
  Apathetic |         82        6.77       85.38
     Oppose |        177       14.62      100.00
------------+-----------------------------------
      Total |      1,211      100.00

. * Tunisian Revolution
. * By age
. mlogit tpartic4 gender newagelvl if country==10 [pw=WT], rrr b(2)

Iteration 0:   log pseudolikelihood = -1029.9264  
Iteration 1:   log pseudolikelihood = -969.25729  
Iteration 2:   log pseudolikelihood = -963.90743  
Iteration 3:   log pseudolikelihood = -963.88572  
Iteration 4:   log pseudolikelihood = -963.88572  

Multinomial logistic regression                 Number of obs     =      1,154
                                                Wald chi2(6)      =     105.93
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -963.88572               Pseudo R2         =     0.0641

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
            gender |   5.430955   1.114705     8.24   0.000     3.632176    8.120551
         newagelvl |   .6762009   .0453783    -5.83   0.000     .5928619    .7712549
             _cons |   .2033012   .0485235    -6.67   0.000     .1273436    .3245658
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
            gender |   .9208609    .177248    -0.43   0.668      .631472     1.34287
         newagelvl |   .9468352   .0600651    -0.86   0.389     .8361344    1.072192
             _cons |   .1970266   .0411233    -7.78   0.000     .1308768     .296611
-------------------+----------------------------------------------------------------
Oppose             |
            gender |   2.382354    .831072     2.49   0.013     1.202456    4.720018
         newagelvl |   .7284675   .1031802    -2.24   0.025     .5518816    .9615557
             _cons |   .0713366   .0275938    -6.83   0.000      .033424    .1522532
------------------------------------------------------------------------------------

. margins, atmeans at(newagelvl=(1 2 3 4 5 6))

Adjusted predictions                            Number of obs     =      1,154
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))

1._at        : gender          =    .4959693 (mean)
               newagelvl       =           1

2._at        : gender          =    .4959693 (mean)
               newagelvl       =           2

3._at        : gender          =    .4959693 (mean)
               newagelvl       =           3

4._at        : gender          =    .4959693 (mean)
               newagelvl       =           4

5._at        : gender          =    .4959693 (mean)
               newagelvl       =           5

6._at        : gender          =    .4959693 (mean)
               newagelvl       =           6

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .2017459   .0223759     9.02   0.000       .15789    .2456018
        1 2  |   .1491137   .0134001    11.13   0.000       .12285    .1753774
        1 3  |   .1078966   .0104432    10.33   0.000     .0874283     .128365
        1 4  |   .0767842   .0103105     7.45   0.000      .056576    .0969925
        1 5  |   .0539567    .010125     5.33   0.000      .034112    .0738014
        1 6  |   .0375611   .0093138     4.03   0.000     .0193065    .0558158
        2 1  |   .6340348   .0252813    25.08   0.000     .5844845    .6835852
        2 2  |   .6930269   .0168398    41.15   0.000     .6600215    .7260322
        2 3  |   .7415915   .0140739    52.69   0.000     .7140071    .7691758
        2 4  |   .7804645   .0160402    48.66   0.000     .7490263    .8119027
        2 5  |   .8110559   .0198849    40.79   0.000     .7720822    .8500296
        2 6  |   .8349644   .0242156    34.48   0.000     .7875027    .8824261
        3 1  |   .1135413   .0154825     7.33   0.000     .0831962    .1438863
        3 2  |   .1175074   .0115191    10.20   0.000     .0949303    .1400844
        3 3  |   .1190568   .0099243    12.00   0.000     .0996055    .1385081
        3 4  |   .1186361   .0120947     9.81   0.000      .094931    .1423412
        3 5  |   .1167317   .0165318     7.06   0.000       .08433    .1491335
        3 6  |   .1137838   .0216402     5.26   0.000     .0713698    .1561979
        4 1  |   .0506779   .0122063     4.15   0.000     .0267541    .0746018
        4 2  |   .0403521   .0068768     5.87   0.000     .0268738    .0538304
        4 3  |   .0314551   .0059659     5.27   0.000     .0197621    .0431481
        4 4  |   .0241151    .006857     3.52   0.000     .0106756    .0375546
        4 5  |   .0182557   .0074187     2.46   0.014     .0037154     .032796
        4 6  |   .0136907   .0073687     1.86   0.063    -.0007517     .028133
------------------------------------------------------------------------------

. * Average probability for all
. tab tpartic4 if country==10 & e(sample)

          Tunisia: |
Part/Supp/Apath,In |
        act/Oppose |      Freq.     Percent        Cum.
-------------------+-----------------------------------
       Participate |        171       14.82       14.82
           Support |        812       70.36       85.18
Apathetic/inactive |        132       11.44       96.62
            Oppose |         39        3.38      100.00
-------------------+-----------------------------------
             Total |      1,154      100.00

. * Rural vs. urban youth in Egyptian revolution
. tab newagelvl egpartic5 if country==2 & urban==0, row

+----------------+
| Key            |
|----------------|
|   frequency    |
| row percentage |
+----------------+

Age levels |
    (as in |
   Ukraine |          Egypt: Part/Aid/Support/Apath/Oppose
     data) | Participa        Aid    Support  Apathetic     Oppose |     Total
-----------+-------------------------------------------------------+----------
      <=25 |         5          3         93          7         35 |       143 
           |      3.50       2.10      65.03       4.90      24.48 |    100.00 
-----------+-------------------------------------------------------+----------
     26-35 |        14          1        148          8         27 |       198 
           |      7.07       0.51      74.75       4.04      13.64 |    100.00 
-----------+-------------------------------------------------------+----------
     36-45 |         5          5        104         12         19 |       145 
           |      3.45       3.45      71.72       8.28      13.10 |    100.00 
-----------+-------------------------------------------------------+----------
     46-55 |         3          3         91          7         17 |       121 
           |      2.48       2.48      75.21       5.79      14.05 |    100.00 
-----------+-------------------------------------------------------+----------
     56-65 |         3          1         47          7         11 |        69 
           |      4.35       1.45      68.12      10.14      15.94 |    100.00 
-----------+-------------------------------------------------------+----------
      >=66 |         1          0         12          2          4 |        19 
           |      5.26       0.00      63.16      10.53      21.05 |    100.00 
-----------+-------------------------------------------------------+----------
     Total |        31         13        495         43        113 |       695 
           |      4.46       1.87      71.22       6.19      16.26 |    100.00 


. tab newagelvl egpartic5 if country==2 & urban==1, row

+----------------+
| Key            |
|----------------|
|   frequency    |
| row percentage |
+----------------+

Age levels |
    (as in |
   Ukraine |          Egypt: Part/Aid/Support/Apath/Oppose
     data) | Participa        Aid    Support  Apathetic     Oppose |     Total
-----------+-------------------------------------------------------+----------
      <=25 |         9          1         50          7          6 |        73 
           |     12.33       1.37      68.49       9.59       8.22 |    100.00 
-----------+-------------------------------------------------------+----------
     26-35 |        18          4         98          9         24 |       153 
           |     11.76       2.61      64.05       5.88      15.69 |    100.00 
-----------+-------------------------------------------------------+----------
     36-45 |        17          3         70          5         17 |       112 
           |     15.18       2.68      62.50       4.46      15.18 |    100.00 
-----------+-------------------------------------------------------+----------
     46-55 |        12          5         57          9          6 |        89 
           |     13.48       5.62      64.04      10.11       6.74 |    100.00 
-----------+-------------------------------------------------------+----------
     56-65 |         3          1         42          6          9 |        61 
           |      4.92       1.64      68.85       9.84      14.75 |    100.00 
-----------+-------------------------------------------------------+----------
      >=66 |         0          1         22          3          2 |        28 
           |      0.00       3.57      78.57      10.71       7.14 |    100.00 
-----------+-------------------------------------------------------+----------
     Total |        59         15        339         39         64 |       516 
           |     11.43       2.91      65.70       7.56      12.40 |    100.00 


. 
. * =====================================================
. * DATA FOR FIGURE 7.5: OCCUPATION OF REV PARTICIPANTS
. * =====================================================
. * Ukrainian revolutions
. * Figure 7.5
. clear

. use monitoring20052014engmerged.dta

. tab EVA266 partic5a if EVA_vers=="yr2005", col m

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

                      |                 Part/Aid/Support/Apathetic/Oppose
           Occupation | Part in r    Aid rev  Support r  Apathetic  Oppose re          . |     Total
----------------------+------------------------------------------------------------------+----------
Professional politici |         0          0          0          0          2          0 |         2 
                      |      0.00       0.00       0.00       0.00       0.33       0.00 |      0.11 
----------------------+------------------------------------------------------------------+----------
  Enterprise director |         1          0          3          0          4          0 |         8 
                      |      0.36       0.00       0.46       0.00       0.66       0.00 |      0.44 
----------------------+------------------------------------------------------------------+----------
Employee of state app |         1          0          7          0          6          0 |        14 
                      |      0.36       0.00       1.08       0.00       0.99       0.00 |      0.78 
----------------------+------------------------------------------------------------------+----------
 Technical specialist |        18          3         28          8         37          3 |        97 
                      |      6.45       5.17       4.30       5.19       6.12       5.66 |      5.39 
----------------------+------------------------------------------------------------------+----------
Specialist in science |        24          5         36          7         28          5 |       105 
                      |      8.60       8.62       5.53       4.55       4.63       9.43 |      5.83 
----------------------+------------------------------------------------------------------+----------
 Policeman or soldier |         1          0          7          1          7          1 |        17 
                      |      0.36       0.00       1.08       0.65       1.16       1.89 |      0.94 
----------------------+------------------------------------------------------------------+----------
Entrepreneur of big/m |         6          0          3          1          4          0 |        14 
                      |      2.15       0.00       0.46       0.65       0.66       0.00 |      0.78 
----------------------+------------------------------------------------------------------+----------
Engages in small busi |        13          3         17          5         21          1 |        60 
                      |      4.66       5.17       2.61       3.25       3.47       1.89 |      3.33 
----------------------+------------------------------------------------------------------+----------
Office staff assistan |        20          3         44         16         42          6 |       131 
                      |      7.17       5.17       6.76      10.39       6.94      11.32 |      7.28 
----------------------+------------------------------------------------------------------+----------
       Skilled worker |        51         10         83         23        111          6 |       284 
                      |     18.28      17.24      12.75      14.94      18.35      11.32 |     15.78 
----------------------+------------------------------------------------------------------+----------
     Unskilled worker |        15          3         34          8         39          2 |       101 
                      |      5.38       5.17       5.22       5.19       6.45       3.77 |      5.61 
----------------------+------------------------------------------------------------------+----------
Employee of agric ent |         8          3         17          5          8          0 |        41 
                      |      2.87       5.17       2.61       3.25       1.32       0.00 |      2.28 
----------------------+------------------------------------------------------------------+----------
               Farmer |         2          1          1          0          1          0 |         5 
                      |      0.72       1.72       0.15       0.00       0.17       0.00 |      0.28 
----------------------+------------------------------------------------------------------+----------
Student or grad stude |        25          0         14          9         21          3 |        72 
                      |      8.96       0.00       2.15       5.84       3.47       5.66 |      4.00 
----------------------+------------------------------------------------------------------+----------
Non-working pensioner |        48         14        223         33        185         17 |       520 
                      |     17.20      24.14      34.25      21.43      30.58      32.08 |     28.89 
----------------------+------------------------------------------------------------------+----------
            Housewife |         9          6         39         16         29          4 |       103 
                      |      3.23      10.34       5.99      10.39       4.79       7.55 |      5.72 
----------------------+------------------------------------------------------------------+----------
Occasional work here  |        18          2         33          8         28          1 |        90 
                      |      6.45       3.45       5.07       5.19       4.63       1.89 |      5.00 
----------------------+------------------------------------------------------------------+----------
Do not work, no incom |         6          2         25          4         14          0 |        51 
                      |      2.15       3.45       3.84       2.60       2.31       0.00 |      2.83 
----------------------+------------------------------------------------------------------+----------
Registered as unemplo |         7          0         18          7          3          1 |        36 
                      |      2.51       0.00       2.76       4.55       0.50       1.89 |      2.00 
----------------------+------------------------------------------------------------------+----------
                Other |         3          1          8          0         10          1 |        23 
                      |      1.08       1.72       1.23       0.00       1.65       1.89 |      1.28 
----------------------+------------------------------------------------------------------+----------
          Hard to say |         0          1          7          0          1          0 |         9 
                      |      0.00       1.72       1.08       0.00       0.17       0.00 |      0.50 
----------------------+------------------------------------------------------------------+----------
                    . |         3          1          4          3          4          2 |        17 
                      |      1.08       1.72       0.61       1.95       0.66       3.77 |      0.94 
----------------------+------------------------------------------------------------------+----------
                Total |       279         58        651        154        605         53 |     1,800 
                      |    100.00     100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA266 partic5a if EVA_vers=="yr2014", col m

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

                      |                 Part/Aid/Support/Apathetic/Oppose
           Occupation | Part in r    Aid rev  Support r  Apathetic  Oppose re          . |     Total
----------------------+------------------------------------------------------------------+----------
Professional politici |         0          0          0          1          0          0 |         1 
                      |      0.00       0.00       0.00       0.44       0.00       0.00 |      0.06 
----------------------+------------------------------------------------------------------+----------
  Enterprise director |         1          3          6          5          4          0 |        19 
                      |      0.70       2.22       0.83       2.19       0.77       0.00 |      1.06 
----------------------+------------------------------------------------------------------+----------
Employee of state app |         3          2          3          1         10          1 |        20 
                      |      2.10       1.48       0.41       0.44       1.92       2.08 |      1.11 
----------------------+------------------------------------------------------------------+----------
 Technical specialist |        17         16         51         22         27          4 |       137 
                      |     11.89      11.85       7.03       9.65       5.18       8.33 |      7.61 
----------------------+------------------------------------------------------------------+----------
Specialist in science |        13         15         37         14         33          4 |       116 
                      |      9.09      11.11       5.10       6.14       6.33       8.33 |      6.44 
----------------------+------------------------------------------------------------------+----------
 Policeman or soldier |         1          0          3          1          0          0 |         5 
                      |      0.70       0.00       0.41       0.44       0.00       0.00 |      0.28 
----------------------+------------------------------------------------------------------+----------
Entrepreneur of big/m |         1          5          5          2          5          0 |        18 
                      |      0.70       3.70       0.69       0.88       0.96       0.00 |      1.00 
----------------------+------------------------------------------------------------------+----------
Engages in small busi |        13          8         26          4         14          1 |        66 
                      |      9.09       5.93       3.59       1.75       2.69       2.08 |      3.67 
----------------------+------------------------------------------------------------------+----------
Office staff assistan |         2          7         40         12         41          3 |       105 
                      |      1.40       5.19       5.52       5.26       7.87       6.25 |      5.83 
----------------------+------------------------------------------------------------------+----------
       Skilled worker |        28         19         95         27         89          8 |       266 
                      |     19.58      14.07      13.10      11.84      17.08      16.67 |     14.78 
----------------------+------------------------------------------------------------------+----------
     Unskilled worker |         8          2         51         17         34          2 |       114 
                      |      5.59       1.48       7.03       7.46       6.53       4.17 |      6.33 
----------------------+------------------------------------------------------------------+----------
Employee of agric ent |         3          2         14          1          7          0 |        27 
                      |      2.10       1.48       1.93       0.44       1.34       0.00 |      1.50 
----------------------+------------------------------------------------------------------+----------
               Farmer |         1          2          2          0          0          0 |         5 
                      |      0.70       1.48       0.28       0.00       0.00       0.00 |      0.28 
----------------------+------------------------------------------------------------------+----------
Student or grad stude |         6          2         20          6         11          0 |        45 
                      |      4.20       1.48       2.76       2.63       2.11       0.00 |      2.50 
----------------------+------------------------------------------------------------------+----------
Non-working pensioner |        21         22        191         56        143         12 |       445 
                      |     14.69      16.30      26.34      24.56      27.45      25.00 |     24.72 
----------------------+------------------------------------------------------------------+----------
            Housewife |         3          6         51         13         26          5 |       104 
                      |      2.10       4.44       7.03       5.70       4.99      10.42 |      5.78 
----------------------+------------------------------------------------------------------+----------
Occasional work here  |        13          9         49         17         31          1 |       120 
                      |      9.09       6.67       6.76       7.46       5.95       2.08 |      6.67 
----------------------+------------------------------------------------------------------+----------
Do not work, no incom |         5          7         24          9         15          1 |        61 
                      |      3.50       5.19       3.31       3.95       2.88       2.08 |      3.39 
----------------------+------------------------------------------------------------------+----------
Registered as unemplo |         0          0         14          2         10          2 |        28 
                      |      0.00       0.00       1.93       0.88       1.92       4.17 |      1.56 
----------------------+------------------------------------------------------------------+----------
                Other |         3          7         23          7         13          2 |        55 
                      |      2.10       5.19       3.17       3.07       2.50       4.17 |      3.06 
----------------------+------------------------------------------------------------------+----------
          Hard to say |         1          1         13          6          6          1 |        28 
                      |      0.70       0.74       1.79       2.63       1.15       2.08 |      1.56 
----------------------+------------------------------------------------------------------+----------
                    . |         0          0          7          5          2          1 |        15 
                      |      0.00       0.00       0.97       2.19       0.38       2.08 |      0.83 
----------------------+------------------------------------------------------------------+----------
                Total |       143        135        725        228        521         48 |     1,800 
                      |    100.00     100.00     100.00     100.00     100.00     100.00 |    100.00 


. * Statistical overrepresentation of groups
. * Orange
. logit newpartica 5.EVA266 if EVA_vers=="yr2005", nolog or

Logistic regression                             Number of obs     =      1,783
                                                LR chi2(1)        =       4.12
                                                Prob > chi2       =     0.0425
Log likelihood = -767.99905                     Pseudo R2         =     0.0027

------------------------------------------------------------------------------------------------------------
                                newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------------------------+----------------------------------------------------------------
                                    EVA266 |
Specialist in science/culture/health/educ  |   1.668864   .4042188     2.11   0.034     1.038125    2.682824
                                     _cons |   .1775439   .0121125   -25.34   0.000     .1553225    .2029443
------------------------------------------------------------------------------------------------------------

. logit newpartica 10.EVA266  if EVA_vers=="yr2005", nolog or

Logistic regression                             Number of obs     =      1,783
                                                LR chi2(1)        =       1.46
                                                Prob > chi2       =     0.2265
Log likelihood = -769.32588                     Pseudo R2         =     0.0009

---------------------------------------------------------------------------------
     newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
         EVA266 |
Skilled worker  |   1.232918   .2103563     1.23   0.220     .8824805    1.722516
          _cons |   .1775334   .0128148   -23.95   0.000     .1541126    .2045135
---------------------------------------------------------------------------------

. logit newpartica 14.EVA266  if EVA_vers=="yr2005", nolog or

Logistic regression                             Number of obs     =      1,783
                                                LR chi2(1)        =      16.85
                                                Prob > chi2       =     0.0000
Log likelihood = -761.63067                     Pseudo R2         =     0.0109

------------------------------------------------------------------------------------------
              newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
                  EVA266 |
Student or grad student  |   3.079618   .7907501     4.38   0.000     1.861808       5.094
                   _cons |    .172721   .0117826   -25.74   0.000     .1511048    .1974296
------------------------------------------------------------------------------------------

. * Euromaidan
. logit newpartica 4.EVA266  if EVA_vers=="yr2014", nolog or

Logistic regression                             Number of obs     =      1,785
                                                LR chi2(1)        =       2.34
                                                Prob > chi2       =     0.1259
Log likelihood = -525.67629                     Pseudo R2         =     0.0022

---------------------------------------------------------------------------------------
           newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
               EVA266 |
Technical specialist  |   1.550123   .4247037     1.60   0.110     .9060524    2.652033
                _cons |   .0913907   .0081274   -26.90   0.000     .0767723    .1087927
---------------------------------------------------------------------------------------

. logit newpartica 5.EVA266  if EVA_vers=="yr2014", nolog or

Logistic regression                             Number of obs     =      1,785
                                                LR chi2(1)        =       1.63
                                                Prob > chi2       =     0.2019
Log likelihood = -526.03331                     Pseudo R2         =     0.0015

------------------------------------------------------------------------------------------------------------
                                newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------------------------------+----------------------------------------------------------------
                                    EVA266 |
Specialist in science/culture/health/educ  |   1.487416   .4436867     1.33   0.183     .8289425     2.66895
                                     _cons |   .0922775   .0081218   -27.07   0.000     .0776564    .1096514
------------------------------------------------------------------------------------------------------------

. logit newpartica 8.EVA266  if EVA_vers=="yr2014", nolog or

Logistic regression                             Number of obs     =      1,785
                                                LR chi2(1)        =      10.17
                                                Prob > chi2       =     0.0014
Log likelihood = -521.76216                     Pseudo R2         =     0.0097

--------------------------------------------------------------------------------------------
                newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------------+----------------------------------------------------------------
                    EVA266 |
Engages in small business  |   3.013094   .9450997     3.52   0.000     1.629375     5.57191
                     _cons |   .0893536   .0078539   -27.48   0.000     .0752132    .1061525
--------------------------------------------------------------------------------------------

. logit newpartica 10.EVA266  if EVA_vers=="yr2014", nolog or

Logistic regression                             Number of obs     =      1,785
                                                LR chi2(1)        =       4.06
                                                Prob > chi2       =     0.0439
Log likelihood = -524.81692                     Pseudo R2         =     0.0039

---------------------------------------------------------------------------------
     newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
         EVA266 |
Skilled worker  |   1.552082   .3269331     2.09   0.037     1.027108     2.34538
          _cons |   .0881089   .0082871   -25.83   0.000     .0732756    .1059448
---------------------------------------------------------------------------------

. *
. * Egyptian and Tunisian revolutions
. * Fiture 7.5
. clear

. use fullarabbarom2.dta

. tab occdisag egpartic5 if country==2, col m

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

          Original AB |
       occupations w/ |
nonempl (created from |               Egypt: Part/Aid/Support/Apath/Oppose
         q1007,q1005) | Participa        Aid    Support  Apathetic     Oppose          . |     Total
----------------------+------------------------------------------------------------------+----------
Emplyr/dir. of instit |         4          1         13          1          5          1 |        25 
                      |      4.44       3.57       1.56       1.22       2.82      12.50 |      2.05 
----------------------+------------------------------------------------------------------+----------
Professional (lwyr, a |        14          0         38          0         12          0 |        64 
                      |     15.56       0.00       4.56       0.00       6.78       0.00 |      5.25 
----------------------+------------------------------------------------------------------+----------
       Manual laborer |         4          1         43          8         11          0 |        67 
                      |      4.44       3.57       5.16       9.76       6.21       0.00 |      5.50 
----------------------+------------------------------------------------------------------+----------
Agricultural worker/O |         5          1         62          3         21          1 |        93 
                      |      5.56       3.57       7.43       3.66      11.86      12.50 |      7.63 
----------------------+------------------------------------------------------------------+----------
Member of the armed f |         1          0          3          0          0          0 |         4 
                      |      1.11       0.00       0.36       0.00       0.00       0.00 |      0.33 
----------------------+------------------------------------------------------------------+----------
Owner of a shop/groce |         4          2         22          2          7          0 |        37 
                      |      4.44       7.14       2.64       2.44       3.95       0.00 |      3.04 
----------------------+------------------------------------------------------------------+----------
  Government employee |        20          7        108          9          6          2 |       152 
                      |     22.22      25.00      12.95      10.98       3.39      25.00 |     12.47 
----------------------+------------------------------------------------------------------+----------
Private sector employ |        11          2         42          5          5          0 |        65 
                      |     12.22       7.14       5.04       6.10       2.82       0.00 |      5.33 
----------------------+------------------------------------------------------------------+----------
         Craftsperson |         4          3         38          6          7          1 |        59 
                      |      4.44      10.71       4.56       7.32       3.95      12.50 |      4.84 
----------------------+------------------------------------------------------------------+----------
              Retired |         3          2         59          7          7          0 |        78 
                      |      3.33       7.14       7.07       8.54       3.95       0.00 |      6.40 
----------------------+------------------------------------------------------------------+----------
            Housewife |        12          8        324         34         86          3 |       467 
                      |     13.33      28.57      38.85      41.46      48.59      37.50 |     38.31 
----------------------+------------------------------------------------------------------+----------
              Student |         3          1         31          2          2          0 |        39 
                      |      3.33       3.57       3.72       2.44       1.13       0.00 |      3.20 
----------------------+------------------------------------------------------------------+----------
           Unemployed |         5          0         47          5          7          0 |        64 
                      |      5.56       0.00       5.64       6.10       3.95       0.00 |      5.25 
----------------------+------------------------------------------------------------------+----------
                    . |         0          0          4          0          1          0 |         5 
                      |      0.00       0.00       0.48       0.00       0.56       0.00 |      0.41 
----------------------+------------------------------------------------------------------+----------
                Total |        90         28        834         82        177          8 |     1,219 
                      |    100.00     100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab occdisag tpartic4 if country==10, col m

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

          Original AB |
       occupations w/ |
nonempl (created from |         Tunisia: Part/Supp/Apath,Inact/Oppose
         q1007,q1005) | Participa    Support  Apathetic     Oppose          . |     Total
----------------------+-------------------------------------------------------+----------
Emplyr/dir. of instit |        10          8          3          0          0 |        21 
                      |      5.85       0.99       2.27       0.00       0.00 |      1.76 
----------------------+-------------------------------------------------------+----------
Professional (lwyr, a |         8         27          4          1          1 |        41 
                      |      4.68       3.33       3.03       2.56       2.38 |      3.43 
----------------------+-------------------------------------------------------+----------
       Manual laborer |        17         84         14          4          6 |       125 
                      |      9.94      10.34      10.61      10.26      14.29 |     10.45 
----------------------+-------------------------------------------------------+----------
Agricultural worker/O |         1         17          1          1          0 |        20 
                      |      0.58       2.09       0.76       2.56       0.00 |      1.67 
----------------------+-------------------------------------------------------+----------
Member of the armed f |         0          8          3          2          1 |        14 
                      |      0.00       0.99       2.27       5.13       2.38 |      1.17 
----------------------+-------------------------------------------------------+----------
Owner of a shop/groce |        10         56          6          0          5 |        77 
                      |      5.85       6.90       4.55       0.00      11.90 |      6.44 
----------------------+-------------------------------------------------------+----------
  Government employee |        22         42         10          1          2 |        77 
                      |     12.87       5.17       7.58       2.56       4.76 |      6.44 
----------------------+-------------------------------------------------------+----------
Private sector employ |        15         56         10          2          0 |        83 
                      |      8.77       6.90       7.58       5.13       0.00 |      6.94 
----------------------+-------------------------------------------------------+----------
         Craftsperson |        10         24          3          3          1 |        41 
                      |      5.85       2.96       2.27       7.69       2.38 |      3.43 
----------------------+-------------------------------------------------------+----------
              Retired |         6         62          5          2          0 |        75 
                      |      3.51       7.64       3.79       5.13       0.00 |      6.27 
----------------------+-------------------------------------------------------+----------
            Housewife |         6        242         36          7         11 |       302 
                      |      3.51      29.80      27.27      17.95      26.19 |     25.25 
----------------------+-------------------------------------------------------+----------
              Student |        31         56          6          7          2 |       102 
                      |     18.13       6.90       4.55      17.95       4.76 |      8.53 
----------------------+-------------------------------------------------------+----------
           Unemployed |        33        126         29          9         13 |       210 
                      |     19.30      15.52      21.97      23.08      30.95 |     17.56 
----------------------+-------------------------------------------------------+----------
                    . |         2          4          2          0          0 |         8 
                      |      1.17       0.49       1.52       0.00       0.00 |      0.67 
----------------------+-------------------------------------------------------+----------
                Total |       171        812        132         39         42 |     1,196 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. * Statistical overrepresentation of groups
. * Tunisia
. logit participate 13.occdisag if country==10 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,188
                                                Wald chi2(1)      =      30.68
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -508.89667               Pseudo R2         =     0.0276

------------------------------------------------------------------------------
             |               Robust
 participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    occdisag |
    Student  |   3.490662   .7878521     5.54   0.000     2.242793    5.432832
       _cons |   .1637135   .0143571   -20.64   0.000     .1378597    .1944159
------------------------------------------------------------------------------

. logit participate 8.occdisag if country==10 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,188
                                                Wald chi2(1)      =      10.39
                                                Prob > chi2       =     0.0013
Log pseudolikelihood = -518.76328               Pseudo R2         =     0.0088

--------------------------------------------------------------------------------------
                     |               Robust
         participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
            occdisag |
Government employee  |   2.350803   .6233183     3.22   0.001     1.398039    3.952878
               _cons |   .1785417   .0150953   -20.38   0.000     .1512768    .2107206
--------------------------------------------------------------------------------------

. logit participate 1.occdisag if country==10 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,188
                                                Wald chi2(1)      =      12.91
                                                Prob > chi2       =     0.0003
Log pseudolikelihood = -517.89939               Pseudo R2         =     0.0104

---------------------------------------------------------------------------------------------
                            |               Robust
                participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------------+----------------------------------------------------------------
                   occdisag |
Emplyr/dir. of institution  |   4.979434   2.225147     3.59   0.000     2.073986    11.95513
                      _cons |   .1838044   .0150088   -20.74   0.000     .1566209     .215706
---------------------------------------------------------------------------------------------

. logit participate 10.occdisag if country==10 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,188
                                                Wald chi2(1)      =       5.60
                                                Prob > chi2       =     0.0180
Log pseudolikelihood = -520.86373               Pseudo R2         =     0.0048

-------------------------------------------------------------------------------
              |               Robust
  participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
     occdisag |
Craftsperson  |   2.315447    .821691     2.37   0.018     1.154957    4.641986
        _cons |   .1844415   .0151558   -20.57   0.000     .1570053    .2166721
-------------------------------------------------------------------------------

. logit participate 14.occdisag if country==10 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,188
                                                Wald chi2(1)      =       2.55
                                                Prob > chi2       =     0.1103
Log pseudolikelihood = -522.11021               Pseudo R2         =     0.0024

------------------------------------------------------------------------------
             |               Robust
 participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    occdisag |
 Unemployed  |   1.370196   .2702587     1.60   0.110     .9308739    2.016854
       _cons |   .1800521    .016135   -19.13   0.000     .1510495    .2146234
------------------------------------------------------------------------------

. mlogit tpartic4 14.occdisag if country==10 [pw=WT], nolog rrr

Multinomial logistic regression                 Number of obs     =      1,146
                                                Wald chi2(3)      =       4.45
                                                Prob > chi2       =     0.2170
Log pseudolikelihood = -1018.1395               Pseudo R2         =     0.0021

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
          occdisag |
       Unemployed  |   1.304467    .285833     1.21   0.225     .8490224    2.004228
             _cons |    .199419   .0188692   -17.04   0.000     .1656629    .2400535
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
          occdisag |
       Unemployed  |   1.458939   .3406838     1.62   0.106     .9231431    2.305713
             _cons |   .1491033   .0160637   -17.66   0.000      .120721    .1841584
-------------------+----------------------------------------------------------------
Oppose             |
          occdisag |
       Unemployed  |   1.627394   .6415175     1.24   0.217      .751536    3.523999
             _cons |   .0441273    .008303   -16.59   0.000     .0305172    .0638073
------------------------------------------------------------------------------------

. * Egypt
. logit participate 8.occdisag if country==2 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,214
                                                Wald chi2(1)      =       6.74
                                                Prob > chi2       =     0.0094
Log pseudolikelihood = -339.60193               Pseudo R2         =     0.0088

--------------------------------------------------------------------------------------
                     |               Robust
         participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
            occdisag |
Government employee  |   2.022642   .5488943     2.60   0.009     1.188295    3.442816
               _cons |   .0797518   .0097087   -20.77   0.000     .0628229    .1012424
--------------------------------------------------------------------------------------

. logit participate 3.occdisag if country==2 [pw=WT], nolog or

Logistic regression                             Number of obs     =      1,214
                                                Wald chi2(1)      =      24.49
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -332.19952               Pseudo R2         =     0.0304

-----------------------------------------------------------------------------------------------------------------
                                                |               Robust
                                    participate | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------------------------------------+----------------------------------------------------------------
                                       occdisag |
Professional (lwyr, acctnt, teacher, dr, etc.)  |   4.690983   1.465231     4.95   0.000     2.543259    8.652409
                                          _cons |   .0765175   .0091021   -21.61   0.000     .0606048    .0966084
-----------------------------------------------------------------------------------------------------------------

. 
. * ======================================================================
. * DATA FOR FIGURE 7.6: INCOME QUINTILES, CONTROLLING FOR GENDER AND AGE
. * ======================================================================
. * Ukrainian revolutions
. clear

. use monitoring20052014engmerged.dta

. * Orange Revolution
. * By income quintiles
. mlogit partic5a gender newage incomequint if EVA_vers=="yr2005", rrr b(3)

Iteration 0:   log likelihood = -2215.6395  
Iteration 1:   log likelihood =  -2165.634  
Iteration 2:   log likelihood = -2165.0309  
Iteration 3:   log likelihood = -2165.0304  
Iteration 4:   log likelihood = -2165.0304  

Multinomial logistic regression                 Number of obs     =      1,649
                                                LR chi2(12)       =     101.22
                                                Prob > chi2       =     0.0000
Log likelihood = -2165.0304                     Pseudo R2         =     0.0228

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.483737   .2237607     2.62   0.009     1.104048    1.994002
      newage |   .9684246   .0045514    -6.83   0.000     .9595451    .9773864
 incomequint |   1.128527   .0597555     2.28   0.022      1.01728    1.251938
       _cons |    1.01016   .2749094     0.04   0.970     .5925707    1.722026
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.315154   .3792353     0.95   0.342     .7473533    2.314342
      newage |   .9947759   .0086549    -0.60   0.547     .9779564    1.011885
 incomequint |    1.01764   .1062973     0.17   0.867     .8292433    1.248838
       _cons |   .0907116   .0489194    -4.45   0.000     .0315226    .2610376
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .7576997   .1493964    -1.41   0.159     .5148311     1.11514
      newage |   .9701018   .0057588    -5.11   0.000     .9588801    .9814549
 incomequint |   1.062066   .0718133     0.89   0.373     .9302426     1.21257
       _cons |   .7922927   .2653638    -0.70   0.487     .4109523    1.527495
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .9662119   .1149634    -0.29   0.773     .7652324    1.219976
      newage |   .9923355   .0035062    -2.18   0.029     .9854872    .9992315
 incomequint |   1.205931   .0513585     4.40   0.000     1.109357    1.310912
       _cons |   .7529515   .1682056    -1.27   0.204     .4859738    1.166598
------------------------------------------------------------------------------

. margins, atmeans at (incomequint=(1 2 3 4 5))

Adjusted predictions                            Number of obs     =      1,649
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4384475 (mean)
               newage          =     46.1698 (mean)
               incomequint     =           1

2._at        : gender          =    .4384475 (mean)
               newage          =     46.1698 (mean)
               incomequint     =           2

3._at        : gender          =    .4384475 (mean)
               newage          =     46.1698 (mean)
               incomequint     =           3

4._at        : gender          =    .4384475 (mean)
               newage          =     46.1698 (mean)
               incomequint     =           4

5._at        : gender          =    .4384475 (mean)
               newage          =     46.1698 (mean)
               incomequint     =           5

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1400269   .0144562     9.69   0.000     .1116933    .1683604
        1 2  |   .1459793   .0108175    13.49   0.000     .1247773    .1671813
        1 3  |   .1511627   .0092887    16.27   0.000     .1329573    .1693682
        1 4  |    .155466   .0113711    13.67   0.000     .1331791     .177753
        1 5  |   .1588043   .0159956     9.93   0.000     .1274535     .190155
        2 1  |   .0371462   .0083302     4.46   0.000     .0208194     .053473
        2 2  |   .0349202   .0055217     6.32   0.000     .0240978    .0457425
        2 3  |   .0326071    .004483     7.27   0.000     .0238207    .0413936
        2 4  |   .0302402    .005429     5.57   0.000     .0195995     .040881
        2 5  |   .0278544    .007118     3.91   0.000     .0139034    .0418054
        3 1  |   .4544819   .0217137    20.93   0.000      .411924    .4970399
        3 2  |   .4198408    .015011    27.97   0.000     .3904198    .4492618
        3 3  |   .3852356   .0123547    31.18   0.000     .3610209    .4094503
        3 4  |   .3510793   .0151654    23.15   0.000     .3213557    .3808029
        3 5  |   .3177753   .0205142    15.49   0.000     .2775681    .3579824
        4 1  |   .0833831   .0117339     7.11   0.000     .0603852     .106381
        4 2  |   .0818083   .0083219     9.83   0.000     .0654978    .0981189
        4 3  |   .0797243    .006977    11.43   0.000     .0660496    .0933991
        4 4  |   .0771652   .0083751     9.21   0.000     .0607502    .0935801
        4 5  |   .0741802   .0112137     6.62   0.000     .0522017    .0961586
        5 1  |   .2849619   .0190501    14.96   0.000     .2476243    .3222994
        5 2  |   .3174514   .0142705    22.25   0.000     .2894817    .3454211
        5 3  |   .3512702   .0120634    29.12   0.000     .3276265     .374914
        5 4  |   .3860492   .0151795    25.43   0.000      .356298    .4158005
        5 5  |   .4213859   .0221185    19.05   0.000     .3780344    .4647373
------------------------------------------------------------------------------

. * Average probability for all
. margins, atmeans

Adjusted predictions                            Number of obs     =      1,649
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4384475 (mean)
               newage          =     46.1698 (mean)
               incomequint     =    2.956337 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .1509541   .0092825    16.26   0.000     .1327608    .1691474
          2  |   .0327095   .0044807     7.30   0.000     .0239275    .0414915
          3  |   .3867402   .0123473    31.32   0.000     .3625398    .4109405
          4  |   .0798255   .0069749    11.44   0.000      .066155    .0934961
          5  |   .3497707   .0120562    29.01   0.000     .3261411    .3734004
------------------------------------------------------------------------------

. * Euromaidan
. * By income quintiles
. mlogit partic5a gender newage incomequint if EVA_vers=="yr2014", rrr b(3)

Iteration 0:   log likelihood = -2235.4118  
Iteration 1:   log likelihood = -2206.5663  
Iteration 2:   log likelihood = -2206.2566  
Iteration 3:   log likelihood = -2206.2564  

Multinomial logistic regression                 Number of obs     =      1,606
                                                LR chi2(12)       =      58.31
                                                Prob > chi2       =     0.0000
Log likelihood = -2206.2564                     Pseudo R2         =     0.0130

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.703346   .3284378     2.76   0.006      1.16728    2.485598
      newage |   .9827123   .0059583    -2.88   0.004     .9711033      .99446
 incomequint |    1.08218   .0662458     1.29   0.197     .9598276     1.22013
       _cons |   .2583232   .0902689    -3.87   0.000     .1302321    .5123997
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.039562   .2019674     0.20   0.842     .7103589    1.521328
      newage |   .9897434   .0060215    -1.69   0.090     .9780116    1.001616
 incomequint |   1.098136   .0690567     1.49   0.137      .970796    1.242179
       _cons |   .2242412   .0800277    -4.19   0.000     .1114133    .4513298
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .5955497   .1002101    -3.08   0.002     .4282434    .8282193
      newage |   .9976372   .0049743    -0.47   0.635     .9879352    1.007434
 incomequint |   1.033292   .0547349     0.62   0.536     .9313943    1.146337
       _cons |   .3696633   .1091601    -3.37   0.001     .2072287    .6594212
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .8285494   .1027065    -1.52   0.129     .6498363    1.056411
      newage |   1.000282   .0038098     0.07   0.941     .9928429    1.007777
 incomequint |   1.196705   .0481908     4.46   0.000     1.105884    1.294984
       _cons |    .418441   .0976601    -3.73   0.000      .264833    .6611445
------------------------------------------------------------------------------

. margins, atmeans at(incomequint=(1 2 3 4 5))

Adjusted predictions                            Number of obs     =      1,606
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4433375 (mean)
               newage          =    45.94707 (mean)
               incomequint     =           1

2._at        : gender          =    .4433375 (mean)
               newage          =    45.94707 (mean)
               incomequint     =           2

3._at        : gender          =    .4433375 (mean)
               newage          =    45.94707 (mean)
               incomequint     =           3

4._at        : gender          =    .4433375 (mean)
               newage          =    45.94707 (mean)
               incomequint     =           4

5._at        : gender          =    .4433375 (mean)
               newage          =    45.94707 (mean)
               incomequint     =           5

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0773487     .01036     7.47   0.000     .0570435    .0976539
        1 2  |   .0787502   .0078789    10.00   0.000     .0633078    .0941925
        1 3  |    .079737   .0070887    11.25   0.000     .0658434    .0936307
        1 4  |   .0802727   .0086325     9.30   0.000     .0633533    .0971921
        1 5  |    .080331   .0116441     6.90   0.000     .0575089    .1031531
        2 1  |   .0759538   .0103023     7.37   0.000     .0557617    .0961459
        2 2  |   .0784702   .0077637    10.11   0.000     .0632535    .0936868
        2 3  |    .080625   .0069208    11.65   0.000     .0670605    .0941895
        2 4  |   .0823633   .0086502     9.52   0.000     .0654092    .0993175
        2 5  |   .0836384   .0120453     6.94   0.000     .0600301    .1072467
        3 1  |   .4868894   .0196896    24.73   0.000     .4482984    .5254803
        3 2  |   .4580671   .0143156    32.00   0.000     .4300091    .4861251
        3 3  |   .4285862   .0126429    33.90   0.000     .4038065    .4533659
        3 4  |   .3986999   .0155735    25.60   0.000     .3681764    .4292233
        3 5  |   .3686904   .0208474    17.69   0.000     .3278302    .4095505
        4 1  |   .1325767   .0134231     9.88   0.000     .1062678    .1588855
        4 2  |    .128881   .0096371    13.37   0.000     .1099926    .1477693
        4 3  |   .1246008   .0084916    14.67   0.000     .1079575    .1412441
        4 4  |    .119771   .0103726    11.55   0.000     .0994411    .1401009
        4 5  |   .1144433    .013692     8.36   0.000     .0876074    .1412791
        5 1  |   .2272315     .01623    14.00   0.000     .1954212    .2590418
        5 2  |   .2558316   .0127607    20.05   0.000     .2308211    .2808422
        5 3  |    .286451   .0114847    24.94   0.000     .2639413    .3089607
        5 4  |   .3188932   .0146159    21.82   0.000     .2902464    .3475399
        5 5  |    .352897   .0211884    16.66   0.000     .3113685    .3944254
------------------------------------------------------------------------------

. * Average probability for all
. margins, atmeans

Adjusted predictions                            Number of obs     =      1,606
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4433375 (mean)
               newage          =    45.94707 (mean)
               incomequint     =    2.837484 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0796065   .0070543    11.28   0.000     .0657803    .0934327
          2  |   .0803018   .0068825    11.67   0.000     .0668123    .0937912
          3  |    .433412   .0125743    34.47   0.000     .4087668    .4580571
          4  |   .1253349   .0084476    14.84   0.000      .108778    .1418919
          5  |   .2813448   .0114195    24.64   0.000      .258963    .3037267
------------------------------------------------------------------------------

. * Egyptian and Tunisian revolutions
. clear

. use fullarabbarom2.dta

. * Egyptian Revolution
. * By income quintiles
. mlogit egpartic5 gender newage incomequintile if country==2 [pw=WT], rrr b(3)

Iteration 0:   log pseudolikelihood = -1209.7412  
Iteration 1:   log pseudolikelihood = -1177.9066  
Iteration 2:   log pseudolikelihood = -1175.6732  
Iteration 3:   log pseudolikelihood = -1175.6663  
Iteration 4:   log pseudolikelihood = -1175.6663  

Multinomial logistic regression                 Number of obs     =      1,211
                                                Wald chi2(12)     =      67.64
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1175.6663               Pseudo R2         =     0.0282

--------------------------------------------------------------------------------
               |               Robust
     egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
Participate    |
        gender |   3.343508   .8648786     4.67   0.000     2.013811     5.55119
        newage |   .9813959   .0078035    -2.36   0.018     .9662199    .9968103
incomequintile |   1.341024   .1168805     3.37   0.001     1.130441    1.590835
         _cons |   .0399667   .0163652    -7.86   0.000     .0179125    .0891745
---------------+----------------------------------------------------------------
Aid            |
        gender |   1.270574   .5083671     0.60   0.549      .579999    2.783381
        newage |   1.005186   .0121459     0.43   0.669     .9816597    1.029275
incomequintile |   1.460957   .2517745     2.20   0.028     1.042187    2.047998
         _cons |   .0070175   .0056366    -6.17   0.000     .0014537    .0338757
---------------+----------------------------------------------------------------
Support        |  (base outcome)
---------------+----------------------------------------------------------------
Apathetic      |
        gender |   .9926121   .2369091    -0.03   0.975     .6217578    1.584667
        newage |   1.013223   .0084127     1.58   0.114     .9968679    1.029846
incomequintile |   .8850794    .079809    -1.35   0.176     .7416996    1.056176
         _cons |   .0788943   .0351171    -5.71   0.000     .0329733    .1887684
---------------+----------------------------------------------------------------
Oppose         |
        gender |   .6602268   .1140269    -2.40   0.016      .470634    .9261964
        newage |   .9938361   .0064379    -0.95   0.340     .9812977    1.006535
incomequintile |   .9276477   .0620328    -1.12   0.261     .8136961    1.057557
         _cons |   .4038616   .1236881    -2.96   0.003      .221585    .7360793
--------------------------------------------------------------------------------

. margins, atmeans at(incomequintile=(1 2 3 4 5))

Adjusted predictions                            Number of obs     =      1,211
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =    .5082399 (mean)
               newage          =    37.88005 (mean)
               incomequin~e    =           1

2._at        : gender          =    .5082399 (mean)
               newage          =    37.88005 (mean)
               incomequin~e    =           2

3._at        : gender          =    .5082399 (mean)
               newage          =    37.88005 (mean)
               incomequin~e    =           3

4._at        : gender          =    .5082399 (mean)
               newage          =    37.88005 (mean)
               incomequin~e    =           4

5._at        : gender          =    .5082399 (mean)
               newage          =    37.88005 (mean)
               incomequin~e    =           5

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0342931   .0075912     4.52   0.000     .0194146    .0491716
        1 2  |   .0462309   .0072254     6.40   0.000     .0320694    .0603923
        1 3  |   .0618229   .0073824     8.37   0.000     .0473536    .0762922
        1 4  |   .0818398   .0107682     7.60   0.000     .0607346     .102945
        1 5  |   .1069679   .0190791     5.61   0.000     .0695737    .1443622
        2 1  |   .0099393   .0047138     2.11   0.035     .0007004    .0191781
        2 2  |   .0145976   .0047566     3.07   0.002     .0052748    .0239203
        2 3  |   .0212667   .0045785     4.64   0.000      .012293    .0302403
        2 4  |   .0306701   .0064123     4.78   0.000     .0181022    .0432381
        2 5  |   .0436723   .0134546     3.25   0.001     .0173016    .0700429
        3 1  |   .7056522    .023317    30.26   0.000     .6599519    .7513526
        3 2  |   .7093815   .0160652    44.16   0.000     .6778944    .7408686
        3 3  |   .7073932   .0139456    50.73   0.000     .6800603    .7347261
        3 4  |   .6982958   .0179622    38.88   0.000     .6630906     .733501
        3 5  |   .6806001   .0264894    25.69   0.000     .6286818    .7325184
        4 1  |   .0807402   .0142421     5.67   0.000     .0528262    .1086543
        4 2  |   .0718392   .0090236     7.96   0.000     .0541532    .0895252
        4 3  |   .0634052   .0074749     8.48   0.000     .0487547    .0780557
        4 4  |   .0553969   .0089651     6.18   0.000     .0378257    .0729681
        4 5  |   .0477882   .0110457     4.33   0.000     .0261391    .0694372
        5 1  |   .1693752   .0199623     8.48   0.000     .1302498    .2085006
        5 2  |   .1579509    .012925    12.22   0.000     .1326184    .1832833
        5 3  |    .146112   .0108331    13.49   0.000     .1248796    .1673445
        5 4  |   .1337974   .0139074     9.62   0.000     .1065394    .1610554
        5 5  |   .1209716   .0184737     6.55   0.000     .0847637    .1571794
------------------------------------------------------------------------------

. * Average probability for all
. margins, atmeans

Adjusted predictions                            Number of obs     =      1,211
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))
at           : gender          =    .5082399 (mean)
               newage          =    37.88005 (mean)
               incomequin~e    =    2.884485 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0598102   .0072592     8.24   0.000     .0455824     .074038
          2  |   .0203717   .0045686     4.46   0.000     .0114174    .0293261
          3  |   .7079582   .0138567    51.09   0.000     .6807994    .7351169
          4  |    .064357   .0074512     8.64   0.000     .0497529    .0789611
          5  |   .1475029   .0107526    13.72   0.000     .1264282    .1685776
------------------------------------------------------------------------------

. * Tunisian Revolution
. * By income quintiles
. mlogit tpartic4 gender newage incomequintile if country==10 [pw=WT], rrr b(2)

Iteration 0:   log pseudolikelihood = -839.94812  
Iteration 1:   log pseudolikelihood = -776.71416  
Iteration 2:   log pseudolikelihood = -770.40319  
Iteration 3:   log pseudolikelihood = -770.35919  
Iteration 4:   log pseudolikelihood = -770.35918  

Multinomial logistic regression                 Number of obs     =        932
                                                Wald chi2(9)      =     103.69
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -770.35918               Pseudo R2         =     0.0828

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
            gender |   5.640642   1.299193     7.51   0.000     3.591482    8.858973
            newage |   .9595056   .0077064    -5.15   0.000     .9445197    .9747293
    incomequintile |   1.273532    .097065     3.17   0.002     1.096816    1.478721
             _cons |   .1515416   .0630351    -4.54   0.000     .0670606    .3424496
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
            gender |   .9789189   .2111784    -0.10   0.921     .6413872    1.494078
            newage |   .9962515   .0076938    -0.49   0.627     .9812854    1.011446
    incomequintile |   1.139678   .0891866     1.67   0.095     .9776209    1.328598
             _cons |   .1282005   .0566184    -4.65   0.000     .0539467    .3046591
-------------------+----------------------------------------------------------------
Oppose             |
            gender |   2.542957    .989905     2.40   0.017     1.185739    5.453672
            newage |   .9581308   .0159003    -2.58   0.010     .9274681    .9898072
    incomequintile |   1.349974   .1784205     2.27   0.023     1.041899    1.749143
             _cons |   .0528006   .0364163    -4.26   0.000     .0136637    .2040369
------------------------------------------------------------------------------------

. margins, atmeans at(incomequintile=(1 2 3 4 5))

Adjusted predictions                            Number of obs     =        932
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))

1._at        : gender          =    .5010537 (mean)
               newage          =    38.79903 (mean)
               incomequin~e    =           1

2._at        : gender          =    .5010537 (mean)
               newage          =    38.79903 (mean)
               incomequin~e    =           2

3._at        : gender          =    .5010537 (mean)
               newage          =    38.79903 (mean)
               incomequin~e    =           3

4._at        : gender          =    .5010537 (mean)
               newage          =    38.79903 (mean)
               incomequin~e    =           4

5._at        : gender          =    .5010537 (mean)
               newage          =    38.79903 (mean)
               incomequin~e    =           5

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0745423   .0143752     5.19   0.000     .0463675    .1027172
        1 2  |   .0912289   .0127133     7.18   0.000     .0663113    .1161466
        1 3  |   .1108284   .0120378     9.21   0.000     .0872347    .1344221
        1 4  |   .1334939   .0153277     8.71   0.000     .1034523    .1635356
        1 5  |   .1592384   .0237133     6.72   0.000     .1127612    .2057157
        2 1  |   .8071319   .0224723    35.92   0.000      .763087    .8511769
        2 2  |   .7756475   .0179854    43.13   0.000     .7403967    .8108982
        2 3  |   .7398994   .0160282    46.16   0.000     .7084846    .7713141
        2 4  |   .6997988   .0203124    34.45   0.000     .6599872    .7396104
        2 5  |    .655465    .030195    21.71   0.000      .596284    .7146461
        3 1  |   .1008553   .0172039     5.86   0.000     .0671362    .1345743
        3 2  |   .1104588   .0130425     8.47   0.000      .084896    .1360217
        3 3  |   .1200856   .0111959    10.73   0.000      .098142    .1420292
        3 4  |   .1294415   .0145645     8.89   0.000     .1008955    .1579875
        3 5  |   .1381758   .0219761     6.29   0.000     .0951034    .1812482
        4 1  |   .0174705   .0070431     2.48   0.013     .0036662    .0312748
        4 2  |   .0226647   .0068532     3.31   0.001     .0092328    .0360967
        4 3  |   .0291867    .006797     4.29   0.000     .0158648    .0425085
        4 4  |   .0372658    .008312     4.48   0.000     .0209745    .0535571
        4 5  |   .0471208   .0130145     3.62   0.000     .0216128    .0726288
------------------------------------------------------------------------------

. * Average probability for all
. margins, atmeans

Adjusted predictions                            Number of obs     =        932
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))
at           : gender          =    .5010537 (mean)
               newage          =    38.79903 (mean)
               incomequin~e    =    2.945266 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .1096772   .0119996     9.14   0.000     .0861584    .1331959
          2  |   .7419686   .0159961    46.38   0.000     .7106169    .7733203
          3  |   .1195627   .0111747    10.70   0.000     .0976608    .1414647
          4  |   .0287915   .0067773     4.25   0.000     .0155082    .0420748
------------------------------------------------------------------------------

. 
. * ===============================================================
. * DATA FOR FIGURE 7.7: CONSUMER GOODS OWNERSHIP, CONTROLLING FOR 
. *   GENDER AND AGE (UKRAINE ONLY)
. * ===============================================================
. clear

. use monitoring20052014engmerged.dta

. * Orange Revolution
. * Number of consumer goods owned
. mlogit partic5a gender newage consumergoods if EVA_vers=="yr2005", rrr b(3)

Iteration 0:   log likelihood = -2367.5224  
Iteration 1:   log likelihood = -2303.4389  
Iteration 2:   log likelihood =  -2301.662  
Iteration 3:   log likelihood = -2301.6592  
Iteration 4:   log likelihood = -2301.6592  

Multinomial logistic regression                 Number of obs     =      1,747
                                                LR chi2(12)       =     131.73
                                                Prob > chi2       =     0.0000
Log likelihood = -2301.6592                     Pseudo R2         =     0.0278

-------------------------------------------------------------------------------
     partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
Part_in_rev   |
       gender |   1.399339   .2079526     2.26   0.024      1.04575    1.872484
       newage |   .9727325   .0045928    -5.86   0.000     .9637723    .9817761
consumergoods |   1.201046    .038947     5.65   0.000     1.127087    1.279859
        _cons |   .4718898   .1434467    -2.47   0.013     .2600695    .8562326
--------------+----------------------------------------------------------------
Aid_rev       |
       gender |   1.285831   .3563568     0.91   0.364     .7469313    2.213538
       newage |   .9990975   .0085203    -0.11   0.916     .9825368    1.015937
consumergoods |   1.104008   .0682725     1.60   0.110     .9779883    1.246267
        _cons |   .0511122   .0305272    -4.98   0.000     .0158539    .1647829
--------------+----------------------------------------------------------------
Support_rev   |  (base outcome)
--------------+----------------------------------------------------------------
Apathetic     |
       gender |   .7827208   .1461798    -1.31   0.190     .5427973    1.128694
       newage |   .9676476    .005484    -5.80   0.000     .9569585     .978456
consumergoods |   .9640812   .0402225    -0.88   0.381     .8883836    1.046229
        _cons |   1.323738   .4595301     0.81   0.419     .6703648    2.613925
--------------+----------------------------------------------------------------
Oppose_rev    |
       gender |   .9564603   .1106539    -0.38   0.700     .7624134    1.199895
       newage |   .9938189   .0034537    -1.78   0.074     .9870728    1.000611
consumergoods |   1.070154   .0279909     2.59   0.010     1.016675    1.126446
        _cons |   .9178366   .2196355    -0.36   0.720     .5742162    1.467085
-------------------------------------------------------------------------------

. margins, atmeans at (consumergoods=(1 2 3 4 5 6 7 8 9 10))

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           1

2._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           2

3._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           3

4._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           4

5._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           5

6._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           6

7._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           7

8._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           8

9._at        : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =           9

10._at       : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =          10

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
       1  1  |   .0837237   .0113764     7.36   0.000     .0614263    .1060211
       1  2  |   .0968387   .0108043     8.96   0.000     .0756628    .1180147
       1  3  |   .1115988   .0100292    11.13   0.000     .0919419    .1312557
       1  4  |    .128109   .0092745    13.81   0.000     .1099312    .1462868
       1  5  |   .1464563   .0090444    16.19   0.000     .1287296    .1641831
       1  6  |   .1667032   .0100638    16.56   0.000     .1469784     .186428
       1  7  |   .1888809   .0127594    14.80   0.000     .1638729    .2138889
       1  8  |   .2129837   .0170141    12.52   0.000     .1796367    .2463306
       1  9  |   .2389632   .0225384    10.60   0.000     .1947887    .2831377
       1 10  |   .2667254   .0290896     9.17   0.000     .2097108      .32374
       2  1  |   .0271635   .0075303     3.61   0.000     .0124044    .0419225
       2  2  |   .0288801   .0065566     4.40   0.000     .0160294    .0417308
       2  3  |    .030593   .0055769     5.49   0.000     .0196624    .0415235
       2  4  |   .0322816   .0047685     6.77   0.000     .0229354    .0416277
       2  5  |   .0339231   .0044511     7.62   0.000     .0251992    .0426471
       2  6  |   .0354931   .0049354     7.19   0.000     .0258199    .0451664
       2  7  |   .0369659   .0061978     5.96   0.000     .0248185    .0491133
       2  8  |   .0383153   .0079908     4.79   0.000     .0226536     .053977
       2  9  |   .0395157   .0101111     3.91   0.000     .0196983    .0593331
       2 10  |    .040543   .0124343     3.26   0.001     .0161722    .0649137
       3  1  |   .4486663   .0254511    17.63   0.000     .3987831    .4985495
       3  2  |   .4320802   .0204057    21.17   0.000     .3920859    .4720746
       3  3  |   .4145865   .0160838    25.78   0.000     .3830628    .4461102
       3  4  |   .3962557   .0130299    30.41   0.000     .3707175    .4217939
       3  5  |   .3771762    .011998    31.44   0.000     .3536606    .4006918
       3  6  |   .3574542   .0132021    27.08   0.000     .3315785    .3833298
       3  7  |   .3372134   .0158907    21.22   0.000     .3060681    .3683587
       3  8  |   .3165945   .0192076    16.48   0.000     .2789483    .3542407
       3  9  |   .2957525    .022643    13.06   0.000     .2513731    .3401319
       3 10  |    .274854   .0259275    10.60   0.000     .2240371    .3256709
       4  1  |   .1147337   .0169408     6.77   0.000     .0815303    .1479372
       4  2  |   .1065236   .0128858     8.27   0.000     .0812678    .1317793
       4  3  |   .0985394   .0097103    10.15   0.000     .0795076    .1175712
       4  4  |   .0907996   .0076775    11.83   0.000      .075752    .1058472
       4  5  |   .0833233   .0070026    11.90   0.000     .0695984    .0970481
       4  6  |     .07613   .0074449    10.23   0.000     .0615384    .0907217
       4  7  |   .0692395   .0084126     8.23   0.000     .0527511     .085728
       4  8  |   .0626709   .0094579     6.63   0.000     .0441339     .081208
       4  9  |   .0564423   .0103643     5.45   0.000     .0361286     .076756
       4 10  |   .0505699   .0110469     4.58   0.000     .0289183    .0722215
       5  1  |   .3257128   .0231135    14.09   0.000     .2804111    .3710145
       5  2  |   .3356774   .0190473    17.62   0.000     .2983454    .3730093
       5  3  |   .3446823   .0154196    22.35   0.000     .3144604    .3749043
       5  4  |   .3525541   .0127532    27.64   0.000     .3275582      .37755
       5  5  |    .359121   .0118156    30.39   0.000     .3359629    .3822792
       5  6  |   .3642195   .0130371    27.94   0.000     .3386672    .3897718
       5  7  |   .3677003   .0159629    23.03   0.000     .3364135     .398987
       5  8  |   .3694356    .019892    18.57   0.000     .3304481    .4084231
       5  9  |   .3693262   .0243939    15.14   0.000     .3215151    .4171374
       5 10  |   .3673077   .0292648    12.55   0.000     .3099499    .4246656
------------------------------------------------------------------------------

. * Average probability for all
. margins, atmeans

Adjusted predictions                            Number of obs     =      1,747
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4436176 (mean)
               newage          =    45.57584 (mean)
               consumergo~s    =    4.962793 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |     .14574    .009035    16.13   0.000     .1280316    .1634483
          2  |   .0338632   .0044497     7.61   0.000     .0251419    .0425845
          3  |   .3778983   .0119941    31.51   0.000     .3543903    .4014064
          4  |   .0835965   .0070044    11.93   0.000     .0698681    .0973249
          5  |    .358902   .0118117    30.39   0.000     .3357515    .3820525
------------------------------------------------------------------------------

. * Euromaidan
. * Number of consumer goods owned
. mlogit partic5a gender newage consumergoods if EVA_vers=="yr2014", rrr b(3)

Iteration 0:   log likelihood = -2440.8253  
Iteration 1:   log likelihood = -2399.4067  
Iteration 2:   log likelihood = -2398.2931  
Iteration 3:   log likelihood = -2398.2924  
Iteration 4:   log likelihood = -2398.2924  

Multinomial logistic regression                 Number of obs     =      1,752
                                                LR chi2(12)       =      85.07
                                                Prob > chi2       =     0.0000
Log likelihood = -2398.2924                     Pseudo R2         =     0.0174

-------------------------------------------------------------------------------
     partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
Part_in_rev   |
       gender |   1.622262   .3041853     2.58   0.010      1.12335    2.342757
       newage |   .9856874   .0059225    -2.40   0.016     .9741477    .9973639
consumergoods |   1.118783   .0445863     2.82   0.005     1.034722    1.209675
        _cons |   .1525906   .0613671    -4.67   0.000     .0693747     .335625
--------------+----------------------------------------------------------------
Aid_rev       |
       gender |    .985963   .1871549    -0.07   0.941     .6796512    1.430326
       newage |   .9952138   .0060128    -0.79   0.427     .9834985    1.007069
consumergoods |   1.173466   .0477027     3.94   0.000     1.083598    1.270788
        _cons |      .0927   .0386418    -5.71   0.000     .0409504    .2098463
--------------+----------------------------------------------------------------
Support_rev   |  (base outcome)
--------------+----------------------------------------------------------------
Apathetic     |
       gender |   .6203296   .0988359    -3.00   0.003     .4539439    .8477013
       newage |   .9920859   .0047759    -1.65   0.099     .9827692    1.001491
consumergoods |   .8755223   .0315608    -3.69   0.000     .8157989     .939618
        _cons |   1.066977   .3438462     0.20   0.841      .567342    2.006619
--------------+----------------------------------------------------------------
Oppose_rev    |
       gender |   .8643999   .1007003    -1.25   0.211     .6879423    1.086119
       newage |   .9991571   .0036221    -0.23   0.816      .992083    1.006282
consumergoods |   .9575995   .0248954    -1.67   0.096     .9100276    1.007658
        _cons |   .9984317   .2477324    -0.01   0.995     .6139273    1.623752
-------------------------------------------------------------------------------

. margins, atmeans at(consumergoods=(1 2 3 4 5 6 7 8 9 10))

Adjusted predictions                            Number of obs     =      1,752
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           1

2._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           2

3._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           3

4._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           4

5._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           5

6._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           6

7._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           7

8._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           8

9._at        : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =           9

10._at       : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =          10

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
       1  1  |   .0423721   .0084112     5.04   0.000     .0258864    .0588578
       1  2  |   .0488002   .0080726     6.05   0.000     .0329781    .0646222
       1  3  |   .0559343     .00756     7.40   0.000     .0411169    .0707517
       1  4  |   .0637922   .0069867     9.13   0.000     .0500986    .0774858
       1  5  |   .0723763   .0066391    10.90   0.000     .0593639    .0853888
       1  6  |   .0816704   .0070176    11.64   0.000     .0679161    .0954247
       1  7  |   .0916353    .008571    10.69   0.000     .0748365    .1084342
       1  8  |   .1022066   .0113588     9.00   0.000     .0799437    .1244694
       1  9  |   .1132915   .0152143     7.45   0.000     .0834719     .143111
       1 10  |   .1247687   .0199855     6.24   0.000     .0855979    .1639395
       2  1  |   .0335943   .0070713     4.75   0.000     .0197347    .0474538
       2  2  |   .0405818   .0071234     5.70   0.000     .0266203    .0545434
       2  3  |    .048788   .0069774     6.99   0.000     .0351126    .0624635
       2  4  |   .0583616   .0066849     8.73   0.000     .0452594    .0714638
       2  5  |   .0694514   .0064691    10.74   0.000     .0567722    .0821306
       2  6  |   .0822003   .0068547    11.99   0.000     .0687654    .0956353
       2  7  |   .0967379   .0085147    11.36   0.000     .0800494    .1134264
       2  8  |   .1131715   .0117647     9.62   0.000     .0901131      .13623
       2  9  |   .1315771   .0165594     7.95   0.000     .0991213    .1640328
       2 10  |   .1519894   .0228039     6.67   0.000     .1072946    .1966841
       3  1  |   .3870926    .025439    15.22   0.000     .3372331     .436952
       3  2  |   .3984836   .0209174    19.05   0.000     .3574862    .4394809
       3  3  |   .4082455    .016869    24.20   0.000     .3751828    .4413082
       3  4  |   .4161642   .0137155    30.34   0.000     .3892823     .443046
       3  5  |   .4220344    .012122    34.82   0.000     .3982757    .4457931
       3  6  |   .4256668   .0126327    33.70   0.000     .4009071    .4504264
       3  7  |   .4268961   .0150134    28.43   0.000     .3974704    .4563218
       3  8  |   .4255906   .0185888    22.90   0.000     .3891573    .4620239
       3  9  |   .4216619   .0228812    18.43   0.000     .3768156    .4665083
       3 10  |   .4150751   .0276636    15.00   0.000     .3608555    .4692947
       4  1  |   .2032223   .0239387     8.49   0.000     .1563033    .2501413
       4  2  |   .1831615   .0178485    10.26   0.000      .148179     .218144
       4  3  |   .1642904   .0129918    12.65   0.000     .1388269     .189754
       4  4  |     .14663   .0096956    15.12   0.000     .1276269    .1656331
       4  5  |   .1301887   .0082956    15.69   0.000     .1139296    .1464477
       4  6  |   .1149641   .0085318    13.47   0.000     .0982421    .1316861
       4  7  |   .1009443   .0095166    10.61   0.000     .0822921    .1195965
       4  8  |   .0881087   .0105591     8.34   0.000     .0674133    .1088042
       4  9  |   .0764291   .0113577     6.73   0.000     .0541685    .0986897
       4 10  |   .0658701   .0118208     5.57   0.000     .0427018    .0890384
       5  1  |   .3337188   .0252233    13.23   0.000      .284282    .3831557
       5  2  |    .328973   .0203705    16.15   0.000     .2890474    .3688985
       5  3  |   .3227417   .0161255    20.01   0.000     .2911363    .3543471
       5  4  |    .315052   .0128775    24.47   0.000     .2898126    .3402915
       5  5  |   .3059492   .0112622    27.17   0.000     .2838757    .3280227
       5  6  |   .2954984   .0117175    25.22   0.000     .2725324    .3184644
       5  7  |   .2837863   .0138185    20.54   0.000     .2567026      .31087
       5  8  |   .2709226   .0167568    16.17   0.000     .2380798    .3037653
       5  9  |   .2570404   .0199758    12.87   0.000     .2178887    .2961922
       5 10  |   .2422968   .0231759    10.45   0.000     .1968728    .2877208
------------------------------------------------------------------------------

. * Average probability for all
. margins, atmeans

Adjusted predictions                            Number of obs     =      1,752
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4452055 (mean)
               newage          =    45.76998 (mean)
               consumergo~s    =    5.296804 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0750621   .0066501    11.29   0.000      .062028    .0880961
          2  |    .073056    .006489    11.26   0.000     .0603377    .0857743
          3  |    .423354   .0120471    35.14   0.000     .3997421     .446966
          4  |   .1255434   .0082306    15.25   0.000     .1094118     .141675
          5  |   .3029845   .0111827    27.09   0.000     .2810669    .3249022
------------------------------------------------------------------------------

. 
. * ======================================================================
. * DATA FOR FIGURE 7.8: EDUCATION LEVELS, CONTROLLING FOR GENDER AND AGE
. * ======================================================================
. * Ukrainian revolutions
. clear

. use monitoring20052014engmerged.dta

. * Orange Revolution
. * Educational levels
. mlogit partic5a gender newage edulevel3 if EVA_vers=="yr2005", rrr b(3)

Iteration 0:   log likelihood = -2366.4614  
Iteration 1:   log likelihood = -2315.0118  
Iteration 2:   log likelihood = -2313.8394  
Iteration 3:   log likelihood = -2313.8374  
Iteration 4:   log likelihood = -2313.8374  

Multinomial logistic regression                 Number of obs     =      1,746
                                                LR chi2(12)       =     105.25
                                                Prob > chi2       =     0.0000
Log likelihood = -2313.8374                     Pseudo R2         =     0.0222

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.484151   .2184017     2.68   0.007     1.112292    1.980329
      newage |   .9747866    .004865    -5.12   0.000      .965298    .9843686
   edulevel3 |   1.561481   .1997938     3.48   0.000     1.215134    2.006547
       _cons |   .4802501   .1869641    -1.88   0.060     .2239185    1.030019
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.348881   .3724904     1.08   0.278     .7850844     2.31756
      newage |   .9945201   .0092584    -0.59   0.555     .9765385    1.012833
   edulevel3 |   .9034257   .2263105    -0.41   0.685     .5529224    1.476117
       _cons |   .1197065   .0916158    -2.77   0.006     .0267092    .5365051
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .7650179   .1424223    -1.44   0.150     .5311346    1.101891
      newage |   .9716338   .0060348    -4.63   0.000     .9598776     .983534
   edulevel3 |   1.248163   .2022927     1.37   0.171     .9084789    1.714855
       _cons |   .6322749   .3058641    -0.95   0.343     .2449828    1.631835
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .9747333   .1122891    -0.22   0.824     .7777276    1.221642
      newage |   .9936051   .0038131    -1.67   0.095     .9861596    1.001107
   edulevel3 |   1.097214   .1112188     0.92   0.360     .8995171     1.33836
       _cons |   1.085252   .3409906     0.26   0.795     .5862453    2.009007
------------------------------------------------------------------------------

. margins, atmeans at (edulevel3=(1 2 3))

Adjusted predictions                            Number of obs     =      1,746
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel3       =           1

2._at        : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel3       =           2

3._at        : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel3       =           3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .1141992   .0123993     9.21   0.000      .089897    .1385014
        1 2  |   .1600034   .0097313    16.44   0.000     .1409304    .1790763
        1 3  |   .2186472   .0255012     8.57   0.000     .1686657    .2686287
        2 1  |   .0393537   .0082598     4.76   0.000     .0231649    .0555425
        2 2  |   .0319012   .0047469     6.72   0.000     .0225975     .041205
        2 3  |   .0252219   .0084748     2.98   0.003     .0086117    .0418322
        3 1  |   .4093809   .0203832    20.08   0.000     .3694306    .4493313
        3 2  |   .3673305   .0128581    28.57   0.000     .3421291    .3925319
        3 3  |    .321466   .0267261    12.03   0.000     .2690838    .3738483
        4 1  |   .0772902   .0108129     7.15   0.000     .0560974     .098483
        4 2  |   .0865616   .0075196    11.51   0.000     .0718234    .1012997
        4 3  |   .0945528   .0173924     5.44   0.000     .0604643    .1286412
        5 1  |    .359776   .0197099    18.25   0.000     .3211453    .3984066
        5 2  |   .3542034   .0126704    27.96   0.000     .3293699    .3790368
        5 3  |    .340112   .0274207    12.40   0.000     .2863685    .3938556
------------------------------------------------------------------------------

. * Average probability for all
. tab partic5a if e(sample)

Part/Aid/Su |
pport/Apath |
etic/Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        279       15.98       15.98
    Aid rev |         58        3.32       19.30
Support rev |        651       37.29       56.59
  Apathetic |        154        8.82       65.41
 Oppose rev |        604       34.59      100.00
------------+-----------------------------------
      Total |      1,746      100.00

. * Euromaidan
. * Educational levels
. mlogit partic5a gender newage edulevel3 if EVA_vers=="yr2014", rrr b(3)

Iteration 0:   log likelihood = -2417.9357  
Iteration 1:   log likelihood = -2395.0629  
Iteration 2:   log likelihood = -2394.6257  
Iteration 3:   log likelihood = -2394.6252  
Iteration 4:   log likelihood = -2394.6252  

Multinomial logistic regression                 Number of obs     =      1,739
                                                LR chi2(12)       =      46.62
                                                Prob > chi2       =     0.0000
Log likelihood = -2394.6252                     Pseudo R2         =     0.0096

------------------------------------------------------------------------------
    partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Part_in_rev  |
      gender |   1.666627   .3153845     2.70   0.007     1.150167    2.414992
      newage |   .9853954   .0059628    -2.43   0.015     .9737776    .9971518
   edulevel3 |   1.546039   .2811937     2.40   0.017      1.08244    2.208194
       _cons |   .1082871    .059522    -4.04   0.000     .0368721    .3180206
-------------+----------------------------------------------------------------
Aid_rev      |
      gender |   1.054753   .2021157     0.28   0.781     .7245032     1.53554
      newage |   .9943297   .0060625    -0.93   0.351     .9825182    1.006283
   edulevel3 |   1.735178   .3169889     3.02   0.003     1.212951    2.482246
       _cons |   .0676984   .0380778    -4.79   0.000     .0224807    .2038671
-------------+----------------------------------------------------------------
Support_rev  |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   .6289806    .100364    -2.91   0.004     .4600597    .8599243
      newage |   .9960006   .0048326    -0.83   0.409     .9865738    1.005517
   edulevel3 |   .9998485   .1487097    -0.00   0.999     .7470214    1.338244
       _cons |   .4516279   .2006499    -1.79   0.074     .1890635    1.078832
-------------+----------------------------------------------------------------
Oppose_rev   |
      gender |   .8498235   .0995902    -1.39   0.165     .6754249    1.069253
      newage |   1.000335   .0036534     0.09   0.927        .9932    1.007521
   edulevel3 |   1.083434   .1219701     0.71   0.477     .8689129    1.350916
       _cons |   .6355174   .2153195    -1.34   0.181     .3271388     1.23459
------------------------------------------------------------------------------

. margins, atmeans at(edulevel3=(1 2 3))

Adjusted predictions                            Number of obs     =      1,739
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel3       =           1

2._at        : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel3       =           2

3._at        : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel3       =           3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0496645    .011321     4.39   0.000     .0274757    .0718533
        1 2  |   .0708413   .0068995    10.27   0.000     .0573185     .084364
        1 3  |   .0982778   .0139329     7.05   0.000     .0709699    .1255857
        2 1  |   .0429973   .0100354     4.28   0.000     .0233282    .0626664
        2 2  |   .0688343   .0067178    10.25   0.000     .0556677    .0820009
        2 3  |    .107176   .0145812     7.35   0.000     .0785974    .1357547
        3 1  |   .4637804   .0306507    15.13   0.000     .4037061    .5238546
        3 2  |   .4278901   .0127313    33.61   0.000     .4029373     .452843
        3 3  |   .3839554   .0218241    17.59   0.000     .3411809    .4267299
        4 1  |   .1418896   .0216332     6.56   0.000     .0994892    .1842899
        4 2  |   .1308894   .0086766    15.09   0.000     .1138835    .1478953
        4 3  |   .1174322   .0141889     8.28   0.000     .0896225    .1452419
        5 1  |   .3016683   .0279227    10.80   0.000     .2469409    .3563957
        5 2  |   .3015448   .0118057    25.54   0.000      .278406    .3246836
        5 3  |   .2931586   .0204364    14.34   0.000      .253104    .3332132
------------------------------------------------------------------------------

. * Average probability for all
. tab partic5a if e(sample)

Part/Aid/Su |
pport/Apath |
etic/Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Part in rev |        141        8.11        8.11
    Aid rev |        133        7.65       15.76
Support rev |        723       41.58       57.33
  Apathetic |        225       12.94       70.27
 Oppose rev |        517       29.73      100.00
------------+-----------------------------------
      Total |      1,739      100.00

. * Egyptian and Tunisian revolutions
. clear

. use fullarabbarom2.dta

. * Egyptian Revolution
. * Educational levels
. mlogit egpartic5 gender newage edulvl3 if country==2 [pw=WT], rrr b(3)

Iteration 0:   log pseudolikelihood = -1206.6323  
Iteration 1:   log pseudolikelihood = -1164.2064  
Iteration 2:   log pseudolikelihood = -1159.7201  
Iteration 3:   log pseudolikelihood = -1159.6975  
Iteration 4:   log pseudolikelihood = -1159.6975  

Multinomial logistic regression                 Number of obs     =      1,208
                                                Wald chi2(12)     =      78.24
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1159.6975               Pseudo R2         =     0.0389

------------------------------------------------------------------------------
             |               Robust
   egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Participate  |
      gender |   2.981759   .8088956     4.03   0.000     1.752094    5.074434
      newage |   .9900576   .0087764    -1.13   0.260     .9730047    1.007409
     edulvl3 |   2.351997   .4189188     4.80   0.000     1.658928    3.334617
       _cons |   .0130588   .0072517    -7.81   0.000     .0043977    .0387779
-------------+----------------------------------------------------------------
Aid          |
      gender |   1.061102   .4444444     0.14   0.887     .4669065    2.411484
      newage |   1.017801   .0138372     1.30   0.194     .9910387    1.045286
     edulvl3 |   2.180935   .6218905     2.73   0.006     1.247165    3.813833
       _cons |   .0033914   .0031277    -6.17   0.000     .0005564    .0206729
-------------+----------------------------------------------------------------
Support      |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   1.060857    .252563     0.25   0.804     .6652844    1.691633
      newage |    1.00751   .0087508     0.86   0.389      .990504    1.024808
     edulvl3 |   .7063594   .1307467    -1.88   0.060      .491438    1.015273
       _cons |   .1241002   .0696906    -3.72   0.000     .0412825    .3730606
-------------+----------------------------------------------------------------
Oppose       |
      gender |   .6965563   .1200451    -2.10   0.036      .496889    .9764568
      newage |    .989509   .0063869    -1.63   0.102     .9770698    1.002107
     edulvl3 |   .7476541   .0948491    -2.29   0.022     .5830629    .9587074
       _cons |    .627555   .2318923    -1.26   0.207     .3041714    1.294748
------------------------------------------------------------------------------

. margins, atmeans at(edulvl3=(1 2 3))

Adjusted predictions                            Number of obs     =      1,208
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =    .5086704 (mean)
               newage          =    37.85118 (mean)
               edulvl3         =           1

2._at        : gender          =    .5086704 (mean)
               newage          =    37.85118 (mean)
               edulvl3         =           2

3._at        : gender          =    .5086704 (mean)
               newage          =    37.85118 (mean)
               edulvl3         =           3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0255911   .0063388     4.04   0.000     .0131672    .0380149
        1 2  |   .0616591   .0079396     7.77   0.000     .0460978    .0772203
        1 3  |   .1371185   .0223072     6.15   0.000     .0933972    .1808399
        2 1  |   .0103712   .0040524     2.56   0.010     .0024287    .0183138
        2 2  |    .023171   .0047194     4.91   0.000     .0139211    .0324209
        2 3  |   .0477804   .0137975     3.46   0.001     .0207378     .074823
        3 1  |   .6976749   .0213283    32.71   0.000     .6558722    .7394775
        3 2  |   .7147014    .014567    49.06   0.000     .6861507    .7432522
        3 3  |   .6757517   .0278388    24.27   0.000     .6211886    .7303148
        4 1  |    .083656   .0135429     6.18   0.000     .0571124    .1101997
        4 2  |   .0605333    .007625     7.94   0.000     .0455887     .075478
        4 3  |    .040428   .0104091     3.88   0.000     .0200267    .0608294
        5 1  |   .1827068   .0180466    10.12   0.000     .1473362    .2180775
        5 2  |   .1399352   .0112974    12.39   0.000     .1177927    .1620778
        5 3  |   .0989214   .0165529     5.98   0.000     .0664782    .1313646
------------------------------------------------------------------------------

. * Average probability for all
. tab egpartic5 if e(sample)

     Egypt: |
Part/Aid/Su |
pport/Apath |
    /Oppose |      Freq.     Percent        Cum.
------------+-----------------------------------
Participate |         89        7.37        7.37
        Aid |         28        2.32        9.69
    Support |        832       68.87       78.56
  Apathetic |         82        6.79       85.35
     Oppose |        177       14.65      100.00
------------+-----------------------------------
      Total |      1,208      100.00

. * Tunisian Revolution
. * Educational levels
. mlogit tpartic4 gender newage edulvl3 if country==10 [pw=WT], rrr b(2)

Iteration 0:   log pseudolikelihood = -1026.3445  
Iteration 1:   log pseudolikelihood = -956.07359  
Iteration 2:   log pseudolikelihood =  -948.6222  
Iteration 3:   log pseudolikelihood = -948.56421  
Iteration 4:   log pseudolikelihood = -948.56418  

Multinomial logistic regression                 Number of obs     =      1,149
                                                Wald chi2(9)      =     115.26
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -948.56418               Pseudo R2         =     0.0758

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
            gender |   5.507531   1.157496     8.12   0.000      3.64807    8.314778
            newage |   .9694358   .0070408    -4.27   0.000     .9557338    .9833342
           edulvl3 |   1.758551    .226666     4.38   0.000     1.365968    2.263963
             _cons |   .0783008    .035981    -5.54   0.000     .0318141    .1927136
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
            gender |   .9280116   .1797511    -0.39   0.700      .634863    1.356522
            newage |   .9936069   .0070052    -0.91   0.363     .9799713    1.007432
           edulvl3 |   .9516424   .1416161    -0.33   0.739     .7108934    1.273923
             _cons |   .2340843   .1060896    -3.20   0.001     .0962938    .5690448
-------------------+----------------------------------------------------------------
Oppose             |
            gender |   2.371715   .8341166     2.46   0.014     1.190421    4.725247
            newage |   .9707386   .0137652    -2.09   0.036     .9441308    .9980964
           edulvl3 |   1.251476   .2624306     1.07   0.285     .8297132    1.887629
             _cons |   .0622021   .0411978    -4.19   0.000     .0169838    .2278109
------------------------------------------------------------------------------------

. margins, atmeans at(edulvl3=(1 2 3))

Adjusted predictions                            Number of obs     =      1,149
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))

1._at        : gender          =    .4980799 (mean)
               newage          =    39.71095 (mean)
               edulvl3         =           1

2._at        : gender          =    .4980799 (mean)
               newage          =    39.71095 (mean)
               edulvl3         =           2

3._at        : gender          =    .4980799 (mean)
               newage          =    39.71095 (mean)
               edulvl3         =           3

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0723892   .0107237     6.75   0.000     .0513712    .0934073
        1 2  |   .1205673   .0116285    10.37   0.000     .0977758    .1433587
        1 3  |   .1937487   .0272895     7.10   0.000     .1402624    .2472351
        2 1  |    .770972   .0186645    41.31   0.000     .7343902    .8075539
        2 2  |   .7301956   .0155182    47.05   0.000     .6997804    .7606108
        2 3  |   .6672579   .0316542    21.08   0.000     .6052167     .729299
        3 1  |   .1282663    .015175     8.45   0.000     .0985238    .1580087
        3 2  |   .1156077   .0109747    10.53   0.000     .0940977    .1371177
        3 3  |   .1005345   .0197023     5.10   0.000     .0619187    .1391503
        4 1  |   .0283725    .007419     3.82   0.000     .0138316    .0429134
        4 2  |   .0336295   .0062965     5.34   0.000     .0212885    .0459705
        4 3  |   .0384589   .0109921     3.50   0.000     .0169149     .060003
------------------------------------------------------------------------------

. * Average probability for all
. tab tpartic4 if e(sample)

          Tunisia: |
Part/Supp/Apath,In |
        act/Oppose |      Freq.     Percent        Cum.
-------------------+-----------------------------------
       Participate |        171       14.88       14.88
           Support |        808       70.32       85.20
Apathetic/inactive |        131       11.40       96.61
            Oppose |         39        3.39      100.00
-------------------+-----------------------------------
             Total |      1,149      100.00

. * Higher education and unemployment (Arab Spring only)
. * Note:  not all in survey were in labor market
. * Egyptian Revolution
. mlogit egpartic5 highered unemployed employed if country==2 [pw=WT], rrr b(3)

Iteration 0:   log pseudolikelihood = -1202.9449  
Iteration 1:   log pseudolikelihood = -1175.0061  
Iteration 2:   log pseudolikelihood = -1168.7048  
Iteration 3:   log pseudolikelihood = -1168.5165  
Iteration 4:   log pseudolikelihood =  -1168.479  
Iteration 5:   log pseudolikelihood =  -1168.471  
Iteration 6:   log pseudolikelihood = -1168.4691  
Iteration 7:   log pseudolikelihood = -1168.4687  
Iteration 8:   log pseudolikelihood = -1168.4686  
Iteration 9:   log pseudolikelihood = -1168.4686  

Multinomial logistic regression                 Number of obs     =      1,203
                                                Wald chi2(12)     =    3306.91
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1168.4686               Pseudo R2         =     0.0287

------------------------------------------------------------------------------
             |               Robust
   egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Participate  |
    highered |   2.810278   .6734305     4.31   0.000     1.757012    4.494939
  unemployed |   2.432473   1.363781     1.59   0.113     .8106189    7.299269
    employed |    3.14726   .8892197     4.06   0.000     1.808989    5.475568
       _cons |   .0377311   .0096939   -12.76   0.000     .0228039    .0624295
-------------+----------------------------------------------------------------
Aid          |
    highered |   2.555109   1.172228     2.04   0.041     1.039673    6.279455
  unemployed |   1.11e-06   4.32e-07   -35.29   0.000     5.19e-07    2.38e-06
    employed |   1.398844   .6208107     0.76   0.449     .5861434    3.338373
       _cons |   .0231261   .0071511   -12.18   0.000     .0126152    .0423948
-------------+----------------------------------------------------------------
Support      |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
    highered |   .6412409    .226957    -1.26   0.209     .3204439    1.283188
  unemployed |   .9459087   .5023796    -0.10   0.917     .3340176    2.678731
    employed |   .9573321   .2323897    -0.18   0.857     .5948887    1.540598
       _cons |   .1034551   .0171715   -13.67   0.000     .0747255    .1432302
-------------+----------------------------------------------------------------
Oppose       |
    highered |    .745577   .1907403    -1.15   0.251     .4515754     1.23099
  unemployed |    .721822   .3061011    -0.77   0.442     .3143861    1.657284
    employed |   .8612064    .153868    -0.84   0.403     .6067738    1.222328
       _cons |   .2448188   .0286107   -12.04   0.000     .1947015    .3078367
------------------------------------------------------------------------------

. margins, atmeans at(highered=1 unemployed=1 employed=0)

Adjusted predictions                            Number of obs     =      1,203
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))
at           : highered        =           1
               unemployed      =           1
               employed        =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .1775828   .0720939     2.46   0.014     .0362813    .3188843
          2  |   4.52e-08   1.27e-08     3.55   0.000     2.02e-08    7.02e-08
          3  |   .6884996   .0740097     9.30   0.000     .5434433     .833556
          4  |   .0432042   .0231586     1.87   0.062    -.0021858    .0885942
          5  |   .0907133   .0388957     2.33   0.020     .0144792    .1669475
------------------------------------------------------------------------------

. margins, atmeans at(highered=1 unemployed=0 employed=1)

Adjusted predictions                            Number of obs     =      1,203
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))
at           : highered        =           1
               unemployed      =           0
               employed        =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .2038501   .0308238     6.61   0.000     .1434366    .2642637
          2  |   .0504907    .016097     3.14   0.002     .0189411    .0820403
          3  |   .6108425   .0350692    17.42   0.000     .5421082    .6795768
          4  |    .038794   .0133225     2.91   0.004     .0126824    .0649056
          5  |   .0960227   .0203303     4.72   0.000      .056176    .1358694
------------------------------------------------------------------------------

. margins, atmeans at(highered=0 unemployed=1 employed=0)

Adjusted predictions                            Number of obs     =      1,203
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))
at           : highered        =           0
               unemployed      =           1
               employed        =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0671714   .0323914     2.07   0.038     .0036854    .1306575
          2  |   1.88e-08   4.84e-09     3.89   0.000     9.32e-09    2.83e-08
          3  |   .7318744   .0581305    12.59   0.000     .6179407    .8458081
          4  |   .0716205   .0336767     2.13   0.033     .0056155    .1376256
          5  |   .1293336   .0455736     2.84   0.005      .040011    .2186563
------------------------------------------------------------------------------

. * Tunisian Revolution
. mlogit tpartic4 highered unemployed employed if country==10 [pw=WT], rrr b(2)

Iteration 0:   log pseudolikelihood = -1016.7469  
Iteration 1:   log pseudolikelihood = -999.87357  
Iteration 2:   log pseudolikelihood = -999.33326  
Iteration 3:   log pseudolikelihood = -999.33255  
Iteration 4:   log pseudolikelihood = -999.33255  

Multinomial logistic regression                 Number of obs     =      1,141
                                                Wald chi2(9)      =      35.50
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -999.33255               Pseudo R2         =     0.0171

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
          highered |    1.87747   .3890472     3.04   0.002       1.2508     2.81811
        unemployed |   1.941309   .5119779     2.52   0.012     1.157734    3.255221
          employed |   2.212717   .4508732     3.90   0.000     1.484162     3.29891
             _cons |   .1122075   .0181354   -13.53   0.000     .0817424    .1540269
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
          highered |    .884035   .2412879    -0.45   0.652     .5177774     1.50937
        unemployed |    1.57512   .4200722     1.70   0.088     .9339099    2.656577
          employed |   1.224375   .2640982     0.94   0.348       .80225    1.868611
             _cons |   .1378263   .0220141   -12.41   0.000     .1007801    .1884904
-------------------+----------------------------------------------------------------
Oppose             |
          highered |    1.55686   .5943746     1.16   0.246     .7366811    3.290178
        unemployed |    1.52275   .6285664     1.02   0.308     .6780574    3.419722
          employed |   .9476708   .3644769    -0.14   0.889     .4459467    2.013873
             _cons |   .0420951    .011346   -11.75   0.000     .0248202    .0713934
------------------------------------------------------------------------------------

. margins, atmeans at(highered=1 unemployed=1 employed=0)

Adjusted predictions                            Number of obs     =      1,141
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))
at           : highered        =           1
               unemployed      =           1
               employed        =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .2404732   .0422045     5.70   0.000     .1577539    .3231926
          2  |   .5879996   .0477871    12.30   0.000     .4943385    .6816607
          3  |   .1128476   .0277174     4.07   0.000     .0585225    .1671726
          4  |   .0586796   .0278131     2.11   0.035      .004167    .1131922
------------------------------------------------------------------------------

. margins, atmeans at(highered=1 unemployed=0 employed=1)

Adjusted predictions                            Number of obs     =      1,141
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))
at           : highered        =           1
               unemployed      =           0
               employed        =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .2778917   .0375741     7.40   0.000     .2042479    .3515356
          2  |   .5961488   .0395669    15.07   0.000     .5185992    .6736985
          3  |   .0889345   .0224158     3.97   0.000     .0450004    .1328686
          4  |   .0370249   .0120308     3.08   0.002      .013445    .0606048
------------------------------------------------------------------------------

. margins, atmeans at(highered=0 unemployed=1 employed=0)

Adjusted predictions                            Number of obs     =      1,141
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))
at           : highered        =           0
               unemployed      =           1
               employed        =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .1453143   .0263104     5.52   0.000     .0937468    .1968819
          2  |   .6671013   .0352975    18.90   0.000     .5979194    .7362831
          3  |    .144823   .0270967     5.34   0.000     .0917144    .1979316
          4  |   .0427614   .0127926     3.34   0.001     .0176884    .0678344
------------------------------------------------------------------------------

. 
. * ============================================================
. * PARTICIPATION, SUPPORT, OPPOSITION BY REGION (UKRAINE ONLY)
. * ============================================================
. clear

. use monitoring20052014engmerged.dta

. mlogit partic5a  gender newage edulevel consumergoods west center south  if EVA_vers=="yr2005", rrr

Iteration 0:   log likelihood = -2366.4614  
Iteration 1:   log likelihood = -1924.6831  
Iteration 2:   log likelihood = -1882.1733  
Iteration 3:   log likelihood = -1879.8565  
Iteration 4:   log likelihood = -1879.8456  
Iteration 5:   log likelihood = -1879.8456  

Multinomial logistic regression                 Number of obs     =      1,746
                                                LR chi2(28)       =     973.23
                                                Prob > chi2       =     0.0000
Log likelihood = -1879.8456                     Pseudo R2         =     0.2056

-------------------------------------------------------------------------------
     partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
Part_in_rev   |
       gender |   1.480125   .2337868     2.48   0.013     1.086052    2.017188
       newage |   .9745159   .0050864    -4.95   0.000     .9645975    .9845362
     edulevel |    1.17485   .0827127     2.29   0.022     1.023424    1.348681
consumergoods |   1.192036   .0415511     5.04   0.000     1.113317    1.276321
         west |   8.470093   2.510539     7.21   0.000     4.737963    15.14205
       center |   2.831332   .8126541     3.63   0.000      1.61316    4.969403
        south |   .6825996    .311665    -0.84   0.403     .2789458    1.670368
        _cons |   .0917359   .0416533    -5.26   0.000     .0376743    .2233742
--------------+----------------------------------------------------------------
Aid_rev       |
       gender |   1.323152   .3729647     0.99   0.321     .7615118    2.299021
       newage |   .9992251   .0092484    -0.08   0.933     .9812619    1.017517
     edulevel |   1.054441   .1400016     0.40   0.690     .8128404    1.367852
consumergoods |   1.117862   .0710044     1.75   0.079     .9870097    1.266061
         west |   10.17401   6.293896     3.75   0.000      3.02634    34.20319
       center |   2.309362   1.463532     1.32   0.187     .6668873    7.997081
        south |   1.925774   1.498345     0.84   0.400     .4191114    8.848735
        _cons |   .0116066   .0106184    -4.87   0.000     .0019319    .0697325
--------------+----------------------------------------------------------------
Support_rev   |  (base outcome)
--------------+----------------------------------------------------------------
Apathetic     |
       gender |   .7644689   .1481424    -1.39   0.166     .5228896     1.11766
       newage |    .970889   .0059582    -4.81   0.000     .9592811    .9826374
     edulevel |   1.037357   .0885742     0.43   0.668     .8775036    1.226331
consumergoods |   .9389236   .0415058    -1.43   0.154     .8609983    1.023902
         west |   .0849971   .0355388    -5.90   0.000     .0374543    .1928885
       center |   .2035482   .0465342    -6.96   0.000     .1300379    .3186139
        south |    .669827   .1716146    -1.56   0.118     .4053951    1.106743
        _cons |   3.140808   1.403712     2.56   0.010     1.308025    7.541652
--------------+----------------------------------------------------------------
Oppose_rev    |
       gender |   .9351292   .1261596    -0.50   0.619     .7178518    1.218172
       newage |   .9962772   .0042539    -0.87   0.382     .9879745     1.00465
     edulevel |   .9488298   .0578604    -0.86   0.389     .8419405    1.069289
consumergoods |   1.042496   .0325991     1.33   0.183     .9805211    1.108387
         west |   .0182239   .0069135   -10.56   0.000     .0086641    .0383316
       center |    .081965   .0133478   -15.36   0.000     .0595679    .1127833
        south |   .5216264   .0922747    -3.68   0.000     .3687939    .7377945
        _cons |   3.609547   1.198504     3.87   0.000     1.882878    6.919638
-------------------------------------------------------------------------------

. margins, atmeans at(west=1 center=0 south=0)

Adjusted predictions                            Number of obs     =      1,746
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel        =    2.172394 (mean)
               consumergo~s    =    4.962772 (mean)
               west            =           1
               center          =           0
               south           =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .4157023   .0293532    14.16   0.000     .3581711    .4732335
          2  |   .1081747   .0180121     6.01   0.000     .0728716    .1434779
          3  |   .4297443   .0292343    14.70   0.000     .3724461    .4870426
          4  |   .0209861   .0079226     2.65   0.008      .005458    .0365141
          5  |   .0253925   .0088884     2.86   0.004     .0079715    .0428136
------------------------------------------------------------------------------

. margins, atmeans at(west=0 center=1 south=0)

Adjusted predictions                            Number of obs     =      1,746
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel        =    2.172394 (mean)
               consumergo~s    =    4.962772 (mean)
               west            =           0
               center          =           1
               south           =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |     .18339   .0169493    10.82   0.000     .1501699    .2166101
          2  |   .0324053   .0075843     4.27   0.000     .0175404    .0472703
          3  |   .5671538   .0214409    26.45   0.000     .5251304    .6091771
          4  |   .0663262   .0105759     6.27   0.000     .0455979    .0870545
          5  |   .1507247   .0153335     9.83   0.000     .1206715    .1807778
------------------------------------------------------------------------------

. margins, atmeans at(west=0 center=0 south=1)

Adjusted predictions                            Number of obs     =      1,746
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel        =    2.172394 (mean)
               consumergo~s    =    4.962772 (mean)
               west            =           0
               center          =           0
               south           =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0243482   .0086942     2.80   0.005     .0073079    .0413885
          2  |   .0148815   .0074276     2.00   0.045     .0003236    .0294394
          3  |   .3123323   .0290367    10.76   0.000     .2554215    .3692432
          4  |   .1201978   .0200883     5.98   0.000     .0808256    .1595701
          5  |   .5282402   .0311807    16.94   0.000     .4671271    .5893532
------------------------------------------------------------------------------

. margins, atmeans at(west=0 center=0 south=0)

Adjusted predictions                            Number of obs     =      1,746
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel        =    2.172394 (mean)
               consumergo~s    =    4.962772 (mean)
               west            =           0
               center          =           0
               south           =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0230447   .0057266     4.02   0.000     .0118208    .0342686
          2  |   .0049924   .0028829     1.73   0.083    -.0006581    .0106429
          3  |    .201784    .016712    12.07   0.000      .169029     .234539
          4  |   .1159321   .0133666     8.67   0.000      .089734    .1421302
          5  |   .6542468   .0197244    33.17   0.000     .6155876     .692906
------------------------------------------------------------------------------

. mlogit partic5a  gender newage edulevel consumergoods west center south  if EVA_vers=="yr2014", rrr

Iteration 0:   log likelihood = -2417.9357  
Iteration 1:   log likelihood = -2077.7262  
Iteration 2:   log likelihood = -2036.1296  
Iteration 3:   log likelihood = -2034.1617  
Iteration 4:   log likelihood = -2034.1326  
Iteration 5:   log likelihood = -2034.1325  

Multinomial logistic regression                 Number of obs     =      1,739
                                                LR chi2(28)       =     767.61
                                                Prob > chi2       =     0.0000
Log likelihood = -2034.1325                     Pseudo R2         =     0.1587

-------------------------------------------------------------------------------
     partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
Part_in_rev   |
       gender |   1.686068   .3327863     2.65   0.008      1.14517    2.482449
       newage |   .9889853   .0063566    -1.72   0.085     .9766047    1.001523
     edulevel |    1.22307   .1013447     2.43   0.015     1.039729    1.438741
consumergoods |   1.146026   .0478683     3.26   0.001     1.055943    1.243793
         west |   8.685271   3.135593     5.99   0.000     4.280348    17.62332
       center |   2.280004   .8307342     2.26   0.024     1.116336     4.65668
        south |   .5852986   .3952051    -0.79   0.428     .1558223    2.198495
        _cons |   .0187383   .0115505    -6.45   0.000     .0055981    .0627219
--------------+----------------------------------------------------------------
Aid_rev       |
       gender |   1.068366    .210849     0.34   0.738     .7256541    1.572933
       newage |    .998254   .0063721    -0.27   0.784     .9858428    1.010821
     edulevel |   1.275475   .1044685     2.97   0.003      1.08631     1.49758
consumergoods |   1.172811    .049101     3.81   0.000     1.080417    1.273106
         west |   15.79886   8.441831     5.17   0.000     5.543728    45.02458
       center |   8.034567   4.227118     3.96   0.000     2.865044    22.53168
        south |   2.979992   1.974061     1.65   0.099     .8134794     10.9165
        _cons |   .0047252   .0034754    -7.28   0.000     .0011178    .0199744
--------------+----------------------------------------------------------------
Support_rev   |  (base outcome)
--------------+----------------------------------------------------------------
Apathetic     |
       gender |   .6033598   .1003308    -3.04   0.002     .4355447     .835834
       newage |      .9903   .0050156    -1.92   0.054     .9805182    1.000179
     edulevel |   .9466797   .0659386    -0.79   0.431     .8258758    1.085154
consumergoods |    .841547   .0324307    -4.48   0.000     .7803251    .9075722
         west |   .1251579   .0343558    -7.57   0.000     .0730809    .2143449
       center |   .2284845    .042316    -7.97   0.000     .1589321    .3284748
        south |   .2621763   .0781698    -4.49   0.000     .1461509    .4703112
        _cons |   4.700647   2.052816     3.54   0.000     1.997239    11.06331
--------------+----------------------------------------------------------------
Oppose_rev    |
       gender |   .7923573   .1058841    -1.74   0.082     .6097804      1.0296
       newage |   .9956497   .0041383    -1.05   0.294     .9875717    1.003794
     edulevel |   .9260959   .0527543    -1.35   0.178     .8282625    1.035485
consumergoods |   .8971481   .0276135    -3.53   0.000     .8446267    .9529355
         west |   .0505905   .0127732   -11.82   0.000      .030843    .0829815
       center |   .0835616   .0138932   -14.93   0.000     .0603231    .1157524
        south |    .437088   .0826997    -4.37   0.000     .3016591    .6333172
        _cons |   7.379696   2.676922     5.51   0.000     3.624702    15.02466
-------------------------------------------------------------------------------

. margins, atmeans at(west=1 center=0 south=0)

Adjusted predictions                            Number of obs     =      1,739
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel        =    3.037378 (mean)
               consumergo~s    =    5.295572 (mean)
               west            =           1
               center          =           0
               south           =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .2298958   .0238699     9.63   0.000     .1831117    .2766799
          2  |   .1694583   .0211621     8.01   0.000     .1279815    .2109352
          3  |   .4902809   .0279497    17.54   0.000     .4355005    .5450613
          4  |   .0500954   .0113531     4.41   0.000     .0278437     .072347
          5  |   .0602696   .0127039     4.74   0.000     .0353704    .0851688
------------------------------------------------------------------------------

. margins, atmeans at(west=0 center=1 south=0)

Adjusted predictions                            Number of obs     =      1,739
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel        =    3.037378 (mean)
               consumergo~s    =    5.295572 (mean)
               west            =           0
               center          =           1
               south           =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0729041   .0107631     6.77   0.000     .0518087    .0939994
          2  |   .1041041   .0128481     8.10   0.000     .0789224    .1292859
          3  |   .5922613   .0205275    28.85   0.000     .5520282    .6324944
          4  |   .1104751     .01303     8.48   0.000     .0849368    .1360135
          5  |   .1202554   .0135037     8.91   0.000     .0937887    .1467221
------------------------------------------------------------------------------

. margins, atmeans at(west=0 center=0 south=1)

Adjusted predictions                            Number of obs     =      1,739
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel        =    3.037378 (mean)
               consumergo~s    =    5.295572 (mean)
               west            =           0
               center          =           0
               south           =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0133168    .007718     1.73   0.084    -.0018102    .0284438
          2  |   .0274744   .0112474     2.44   0.015     .0054298    .0495189
          3  |   .4214251   .0367779    11.46   0.000     .3493417    .4935085
          4  |   .0902003   .0210787     4.28   0.000     .0488869    .1315138
          5  |   .4475834   .0370229    12.09   0.000     .3750198     .520147
------------------------------------------------------------------------------

. margins, atmeans at(west=0 center=0 south=0)

Adjusted predictions                            Number of obs     =      1,739
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))
at           : gender          =    .4439333 (mean)
               newage          =    45.78551 (mean)
               edulevel        =    3.037378 (mean)
               consumergo~s    =    5.295572 (mean)
               west            =           0
               center          =           0
               south           =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    _predict |
          1  |   .0124912   .0040456     3.09   0.002     .0045621    .0204204
          2  |   .0050617   .0025547     1.98   0.048     .0000546    .0100687
          3  |   .2313675   .0171376    13.50   0.000     .1977784    .2649565
          4  |   .1888846   .0159641    11.83   0.000     .1575955    .2201738
          5  |    .562195   .0201269    27.93   0.000     .5227471    .6016429
------------------------------------------------------------------------------

. 
. * ========================================================================
. * DATA FOR FIGURE 7.9: PARTICIPATION, SUPPORT, OPPOSITION BY LANGUAGE USE 
. *   AT HOME (UKRAINE ONLY)
. * ========================================================================
. clear

. use monitoring20052014engmerged.dta

. mlogit partic5a  gender newage edulevel consumergoods ukrspeakathome  if EVA_vers=="yr2005", rrr

Iteration 0:   log likelihood = -2366.4614  
Iteration 1:   log likelihood = -2037.8904  
Iteration 2:   log likelihood = -2022.2983  
Iteration 3:   log likelihood =  -2022.198  
Iteration 4:   log likelihood =  -2022.198  

Multinomial logistic regression                 Number of obs     =      1,746
                                                LR chi2(20)       =     688.53
                                                Prob > chi2       =     0.0000
Log likelihood =  -2022.198                     Pseudo R2         =     0.1455

--------------------------------------------------------------------------------
      partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
Part_in_rev    |
        gender |   1.494754    .228904     2.62   0.009      1.10718       2.018
        newage |   .9723597   .0049662    -5.49   0.000     .9626747    .9821422
      edulevel |   1.166069   .0787901     2.27   0.023     1.021432    1.331187
 consumergoods |   1.216015   .0419443     5.67   0.000     1.136523    1.301067
ukrspeakathome |   3.137825   .5419389     6.62   0.000     2.236745     4.40191
         _cons |   .1432741   .0563766    -4.94   0.000     .0662568     .309817
---------------+----------------------------------------------------------------
Aid_rev        |
        gender |   1.335445   .3715623     1.04   0.298     .7740968    2.303863
        newage |   .9974216    .009127    -0.28   0.778     .9796924    1.015472
      edulevel |    1.02673   .1340068     0.20   0.840      .794985     1.32603
 consumergoods |   1.130487   .0722119     1.92   0.055     .9974558    1.281261
ukrspeakathome |    2.38496   .7649625     2.71   0.007     1.271929    4.471973
         _cons |   .0257419    .019457    -4.84   0.000     .0058514    .1132456
---------------+----------------------------------------------------------------
Support_rev    |  (base outcome)
---------------+----------------------------------------------------------------
Apathetic      |
        gender |   .7300962    .139617    -1.65   0.100     .5018848    1.062077
        newage |   .9727284   .0058933    -4.56   0.000      .961246     .984348
      edulevel |   1.001542   .0846736     0.02   0.985     .8486052    1.182041
 consumergoods |   .9202741   .0400751    -1.91   0.056      .844987    1.002269
ukrspeakathome |   .2301635   .0491016    -6.89   0.000     .1515119    .3496442
         _cons |   2.407614   1.040024     2.03   0.042     1.032502    5.614137
---------------+----------------------------------------------------------------
Oppose_rev     |
        gender |   .8689785    .111191    -1.10   0.272     .6762274    1.116671
        newage |   .9985631   .0040424    -0.36   0.722     .9906714    1.006518
      edulevel |   .8959331    .051862    -1.90   0.058     .7998396    1.003571
 consumergoods |   1.012041   .0298512     0.41   0.685     .9551927    1.072273
ukrspeakathome |   .0887285   .0136979   -15.69   0.000     .0655624    .1200801
         _cons |   2.714424   .8401861     3.23   0.001     1.479818    4.979057
--------------------------------------------------------------------------------

. margins, atmeans at(ukrspeakathome=(0 1))

Adjusted predictions                            Number of obs     =      1,746
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel        =    2.172394 (mean)
               consumergo~s    =    4.962772 (mean)
               ukrspeakat~e    =           0

2._at        : gender          =     .443299 (mean)
               newage          =    45.57847 (mean)
               edulevel        =    2.172394 (mean)
               consumergo~s    =    4.962772 (mean)
               ukrspeakat~e    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0486161   .0065283     7.45   0.000     .0358209    .0614114
        1 2  |    .284382   .0180208    15.78   0.000     .2490619    .3197021
        2 1  |   .0139968   .0036966     3.79   0.000     .0067516    .0212421
        2 2  |   .0622306   .0093942     6.62   0.000     .0438183    .0806429
        3 1  |   .2764208   .0144026    19.19   0.000     .2481921    .3046494
        3 2  |   .5153042   .0194618    26.48   0.000     .4771597    .5534486
        4 1  |   .1090567   .0102788    10.61   0.000     .0889107    .1292027
        4 2  |   .0467931   .0078976     5.93   0.000     .0313142     .062272
        5 1  |   .5519096   .0160882    34.31   0.000     .5203774    .5834418
        5 2  |   .0912901   .0107584     8.49   0.000      .070204    .1123763
------------------------------------------------------------------------------

. mlogit partic5a  gender newage edulevel consumergoods ukrspeakathome  if EVA_vers=="yr2014", rrr

Iteration 0:   log likelihood = -2414.9662  
Iteration 1:   log likelihood =  -2223.672  
Iteration 2:   log likelihood = -2213.3862  
Iteration 3:   log likelihood = -2213.3155  
Iteration 4:   log likelihood = -2213.3155  

Multinomial logistic regression                 Number of obs     =      1,736
                                                LR chi2(20)       =     403.30
                                                Prob > chi2       =     0.0000
Log likelihood = -2213.3155                     Pseudo R2         =     0.0835

--------------------------------------------------------------------------------
      partic5a |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
Part_in_rev    |
        gender |   1.588197   .3046284     2.41   0.016     1.090529    2.312977
        newage |   .9859188   .0061527    -2.27   0.023     .9739332    .9980519
      edulevel |   1.175512   .0945039     2.01   0.044     1.004143    1.376126
 consumergoods |   1.140657   .0472195     3.18   0.001     1.051763    1.237063
ukrspeakathome |   2.829424   .5938698     4.96   0.000     1.875161    4.269306
         _cons |   .0425023   .0223566    -6.00   0.000     .0151591    .1191658
---------------+----------------------------------------------------------------
Aid_rev        |
        gender |    1.00039    .194745     0.00   0.998     .6830719    1.465116
        newage |   .9961001   .0062742    -0.62   0.535     .9838786    1.008474
      edulevel |   1.241997    .100189     2.69   0.007     1.060367    1.454739
 consumergoods |   1.179995   .0499749     3.91   0.000     1.086001    1.282124
ukrspeakathome |   2.612066   .5516593     4.55   0.000     1.726686    3.951436
         _cons |   .0236864   .0129505    -6.85   0.000     .0081116    .0691661
---------------+----------------------------------------------------------------
Support_rev    |  (base outcome)
---------------+----------------------------------------------------------------
Apathetic      |
        gender |   .6359465   .1032208    -2.79   0.005     .4626597     .874137
        newage |    .994295   .0049023    -1.16   0.246      .984733     1.00395
      edulevel |   .9912426   .0668355    -0.13   0.896      .868534    1.131288
 consumergoods |   .8444038   .0318208    -4.49   0.000     .7842838    .9091323
ukrspeakathome |   .3980307   .0656667    -5.58   0.000     .2880622    .5499801
         _cons |   1.746346   .7104264     1.37   0.171     .7867834    3.876192
---------------+----------------------------------------------------------------
Oppose_rev     |
        gender |   .8542415   .1062687    -1.27   0.205     .6694069    1.090112
        newage |   1.001084   .0038837     0.28   0.780     .9935008    1.008725
      edulevel |   .9822968   .0520105    -0.34   0.736     .8854692    1.089713
 consumergoods |    .894853   .0254991    -3.90   0.000     .8462456    .9462524
ukrspeakathome |   .1712323   .0241883   -12.49   0.000     .1298211    .2258533
         _cons |   2.503317   .8060865     2.85   0.004      1.33175    4.705535
--------------------------------------------------------------------------------

. margins, atmeans at(ukrspeakathome=(0 1))

Adjusted predictions                            Number of obs     =      1,736
Model VCE    : OIM

1._predict   : Pr(partic5a==Part_in_rev), predict(pr outcome(1))
2._predict   : Pr(partic5a==Aid_rev), predict(pr outcome(2))
3._predict   : Pr(partic5a==Support_rev), predict(pr outcome(3))
4._predict   : Pr(partic5a==Apathetic), predict(pr outcome(4))
5._predict   : Pr(partic5a==Oppose_rev), predict(pr outcome(5))

1._at        : gender          =    .4441244 (mean)
               newage          =    45.76555 (mean)
               edulevel        =    3.036866 (mean)
               consumergo~s    =    5.297811 (mean)
               ukrspeakat~e    =           0

2._at        : gender          =    .4441244 (mean)
               newage          =    45.76555 (mean)
               edulevel        =    3.036866 (mean)
               consumergo~s    =    5.297811 (mean)
               ukrspeakat~e    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0307778   .0053015     5.81   0.000     .0203871    .0411685
        1 2  |   .1341219   .0130946    10.24   0.000      .108457    .1597869
        2 1  |   .0316189   .0054098     5.84   0.000     .0210159    .0422218
        2 2  |   .1272022   .0126937    10.02   0.000     .1023229    .1520814
        3 1  |   .3438719   .0153849    22.35   0.000     .3137179    .3740258
        3 2  |   .5296156    .018761    28.23   0.000     .4928447    .5663865
        4 1  |   .1502384   .0116501    12.90   0.000     .1274046    .1730723
        4 2  |   .0921005   .0107235     8.59   0.000     .0710829    .1131181
        5 1  |   .4434931   .0161328    27.49   0.000     .4118733    .4751128
        5 2  |   .1169598   .0118605     9.86   0.000     .0937136     .140206
------------------------------------------------------------------------------

. 
. * ====================================================
. * VARIOUS IDENTITY FEATURES OF UKRAINIAN PARTICIPANTS
. * ====================================================
. clear

. use monitoring20052014engmerged.dta

. * Proportion speaking primarily Ukrainian at home
. tab ukrspeakathome partic5a if EVA_vers=="yr2014", col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

    Speaks |
 primarily |
 Ukrainian |           Part/Aid/Support/Apathetic/Oppose
   at home | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |        38         40        338        149        428 |       993 
           |     26.57      29.63      46.75      65.35      82.31 |     56.78 
-----------+-------------------------------------------------------+----------
       yes |       105         95        385         79         92 |       756 
           |     73.43      70.37      53.25      34.65      17.69 |     43.22 
-----------+-------------------------------------------------------+----------
     Total |       143        135        723        228        520 |     1,749 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab ukrspeakathome partic5a if EVA_vers=="yr2005", col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

    Speaks |
 primarily |
 Ukrainian |           Part/Aid/Support/Apathetic/Oppose
   at home | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |        71         15        270        118        535 |     1,009 
           |     25.45      25.86      41.47      76.62      88.43 |     57.76 
-----------+-------------------------------------------------------+----------
       yes |       208         43        381         36         70 |       738 
           |     74.55      74.14      58.53      23.38      11.57 |     42.24 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        154        605 |     1,747 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. * Uniate
. tab uniate partic5a if EVA_vers=="yr2005", col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |           Part/Aid/Support/Apathetic/Oppose
    Uniate | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
         0 |       217         39        615        153        602 |     1,626 
           |     77.78      67.24      94.47      99.35      99.67 |     93.13 
-----------+-------------------------------------------------------+----------
         1 |        62         19         36          1          2 |       120 
           |     22.22      32.76       5.53       0.65       0.33 |      6.87 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        154        604 |     1,746 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab uniate partic5a if EVA_vers=="yr2014", col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |           Part/Aid/Support/Apathetic/Oppose
    Uniate | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
         0 |        97        107        662        227        519 |     1,612 
           |     68.79      79.26      91.69      99.56      99.62 |     92.27 
-----------+-------------------------------------------------------+----------
         1 |        44         28         60          1          2 |       135 
           |     31.21      20.74       8.31       0.44       0.38 |      7.73 
-----------+-------------------------------------------------------+----------
     Total |       141        135        722        228        521 |     1,747 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. * Identifies primarily as citizen of Ukraine
. tab ukrcitizen partic5a if EVA_vers=="yr2005", col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Considers |
   oneself |
 primarily |
         a |
 Ukrainian |           Part/Aid/Support/Apathetic/Oppose
   citizen | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |        69         24        299         78        326 |       796 
           |     24.82      41.38      45.93      50.65      53.88 |     45.59 
-----------+-------------------------------------------------------+----------
       yes |       209         34        352         76        279 |       950 
           |     75.18      58.62      54.07      49.35      46.12 |     54.41 
-----------+-------------------------------------------------------+----------
     Total |       278         58        651        154        605 |     1,746 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab ukrcitizen partic5a if EVA_vers=="yr2014", col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Considers |
   oneself |
 primarily |
         a |
 Ukrainian |           Part/Aid/Support/Apathetic/Oppose
   citizen | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |        25         26        184         98        289 |       622 
           |     17.48      19.26      25.48      43.36      55.58 |     35.62 
-----------+-------------------------------------------------------+----------
       yes |       118        109        538        128        231 |     1,124 
           |     82.52      80.74      74.52      56.64      44.42 |     64.38 
-----------+-------------------------------------------------------+----------
     Total |       143        135        722        226        520 |     1,746 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. * Proud to be Ukrainian citizen
. tab ukrproud partic5a if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Proud to |
      be a |
 Ukrainian |           Part/Aid/Support/Apathetic/Oppose
   citizen | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |        60         10        232         96        401 |       799 
           |     21.58      17.24      35.69      62.34      66.28 |     45.79 
-----------+-------------------------------------------------------+----------
       yes |       218         48        418         58        204 |       946 
           |     78.42      82.76      64.31      37.66      33.72 |     54.21 
-----------+-------------------------------------------------------+----------
     Total |       278         58        650        154        605 |     1,745 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab ukrproud partic5a if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Proud to |
      be a |
 Ukrainian |           Part/Aid/Support/Apathetic/Oppose
   citizen | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |        12         17        153        109        318 |       609 
           |      9.68      13.39      23.65      53.43      69.58 |     39.06 
-----------+-------------------------------------------------------+----------
       yes |       112        110        494         95        139 |       950 
           |     90.32      86.61      76.35      46.57      30.42 |     60.94 
-----------+-------------------------------------------------------+----------
     Total |       124        127        647        204        457 |     1,559 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. * Foreign orientation
. tab fororientation5 partic5a if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Foreign orientation |           Part/Aid/Support/Apathetic/Oppose
                  (5) | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
----------------------+-------------------------------------------------------+----------
    Toward Russia/CIS |        52         10        255         91        436 |       844 
                      |     18.64      17.24      39.17      59.09      72.07 |     48.31 
----------------------+-------------------------------------------------------+----------
Rely on own resources |        79         15        169         30         61 |       354 
                      |     28.32      25.86      25.96      19.48      10.08 |     20.26 
----------------------+-------------------------------------------------------+----------
      Toward the West |       109         25        138         11         35 |       318 
                      |     39.07      43.10      21.20       7.14       5.79 |     18.20 
----------------------+-------------------------------------------------------+----------
                Other |        18          3         19          2         34 |        76 
                      |      6.45       5.17       2.92       1.30       5.62 |      4.35 
----------------------+-------------------------------------------------------+----------
          Hard to say |        21          5         70         20         39 |       155 
                      |      7.53       8.62      10.75      12.99       6.45 |      8.87 
----------------------+-------------------------------------------------------+----------
                Total |       279         58        651        154        605 |     1,747 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab fororientation5 partic5a if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Foreign orientation |           Part/Aid/Support/Apathetic/Oppose
                  (5) | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
----------------------+-------------------------------------------------------+----------
    Toward Russia/CIS |         5          4         64         68        248 |       389 
                      |      3.50       2.96       8.83      29.82      47.60 |     22.20 
----------------------+-------------------------------------------------------+----------
Rely on own resources |        46         63        309         65        132 |       615 
                      |     32.17      46.67      42.62      28.51      25.34 |     35.10 
----------------------+-------------------------------------------------------+----------
      Toward the West |        82         61        241         30         42 |       456 
                      |     57.34      45.19      33.24      13.16       8.06 |     26.03 
----------------------+-------------------------------------------------------+----------
                Other |         8          3         37         11         46 |       105 
                      |      5.59       2.22       5.10       4.82       8.83 |      5.99 
----------------------+-------------------------------------------------------+----------
          Hard to say |         2          4         74         54         53 |       187 
                      |      1.40       2.96      10.21      23.68      10.17 |     10.67 
----------------------+-------------------------------------------------------+----------
                Total |       143        135        725        228        521 |     1,752 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. 
. * =====================================================
. * DATA FOR FIGURE 7.10: RELIGIOUS PRACTICE IN TUNISIAN 
. *   AND EGYPTIANS REVOLUTIONS
. * =====================================================
. clear

. use fullarabbarom2.dta

. mlogit egpartic5 gender newage  religscale christian if country==2 [pw=WT], rrr b(3)

Iteration 0:   log pseudolikelihood = -1206.3169  
Iteration 1:   log pseudolikelihood = -1164.3115  
Iteration 2:   log pseudolikelihood =  -1160.798  
Iteration 3:   log pseudolikelihood = -1160.6491  
Iteration 4:   log pseudolikelihood = -1160.6194  
Iteration 5:   log pseudolikelihood =  -1160.613  
Iteration 6:   log pseudolikelihood = -1160.6116  
Iteration 7:   log pseudolikelihood = -1160.6112  
Iteration 8:   log pseudolikelihood = -1160.6112  
Iteration 9:   log pseudolikelihood = -1160.6111  

Multinomial logistic regression                 Number of obs     =      1,207
                                                Wald chi2(16)     =    3240.62
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1160.6111               Pseudo R2         =     0.0379

------------------------------------------------------------------------------
             |               Robust
   egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Participate  |
      gender |   3.269492   .8559003     4.53   0.000     1.957264    5.461489
      newage |   .9805408   .0077838    -2.48   0.013     .9654029    .9959161
  religscale |   1.085508   .0440135     2.02   0.043     1.002582    1.175293
   christian |   .7347861   .4658889    -0.49   0.627     .2120602    2.546025
       _cons |    .051202   .0246313    -6.18   0.000     .0199437    .1314522
-------------+----------------------------------------------------------------
Aid          |
      gender |   1.172399   .4834881     0.39   0.700     .5224525    2.630899
      newage |   1.004481   .0122646     0.37   0.714     .9807279    1.028809
  religscale |   1.163786   .0717756     2.46   0.014     1.031278    1.313319
   christian |   1.19e-06   3.27e-07   -49.81   0.000     6.98e-07    2.04e-06
       _cons |   .0066187   .0048953    -6.78   0.000     .0015532    .0282052
-------------+----------------------------------------------------------------
Support      |  (base outcome)
-------------+----------------------------------------------------------------
Apathetic    |
      gender |   1.027114   .2449547     0.11   0.911     .6436013    1.639156
      newage |   1.014772   .0087056     1.71   0.087      .997852    1.031979
  religscale |   .8819621   .0441585    -2.51   0.012     .7995241    .9729001
   christian |   2.896803   1.056756     2.92   0.004     1.417098    5.921584
       _cons |   .1326261   .0617442    -4.34   0.000     .0532539    .3302984
-------------+----------------------------------------------------------------
Oppose       |
      gender |   .6653437   .1156928    -2.34   0.019     .4731899    .9355276
      newage |   .9960126   .0063974    -0.62   0.534     .9835525    1.008631
  religscale |   .9030543   .0265095    -3.47   0.001      .852563    .9565358
   christian |   1.938829   .6144969     2.09   0.037     1.041736    3.608455
       _cons |   .6570219   .2305478    -1.20   0.231     .3302895    1.306968
------------------------------------------------------------------------------

. margins, atmeans at(christian=0 religscale=(0 3 6 9 12 15))

Adjusted predictions                            Number of obs     =      1,207
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =           0
               christian       =           0

2._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =           3
               christian       =           0

3._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =           6
               christian       =           0

4._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =           9
               christian       =           0

5._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =          12
               christian       =           0

6._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =          15
               christian       =           0

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0253988   .0097982     2.59   0.010     .0061947    .0446028
        1 2  |   .0361586   .0098005     3.69   0.000     .0169499    .0553672
        1 3  |   .0499438    .008613     5.80   0.000     .0330626     .066825
        1 4  |   .0670113   .0080626     8.31   0.000      .051209    .0828136
        1 5  |   .0874177   .0136895     6.39   0.000     .0605868    .1142486
        1 6  |   .1108782   .0263317     4.21   0.000      .059269    .1624875
        2 1  |   .0048669   .0030221     1.61   0.107    -.0010562    .0107901
        2 2  |   .0085383   .0038247     2.23   0.026     .0010421    .0160345
        2 3  |   .0145332    .004264     3.41   0.001      .006176    .0228905
        2 4  |   .0240297   .0047695     5.04   0.000     .0146817    .0333778
        2 5  |   .0386296   .0092271     4.19   0.000     .0205449    .0567143
        2 6  |   .0603792    .021954     2.75   0.006     .0173501    .1034084
        3 1  |   .5725969   .0521814    10.97   0.000     .4703231    .6748706
        3 2  |   .6373077   .0321834    19.80   0.000     .5742293     .700386
        3 3  |    .688209   .0180696    38.09   0.000     .6527932    .7236247
        3 4  |   .7219179   .0145326    49.68   0.000     .6934345    .7504012
        3 5  |   .7362755   .0206824    35.60   0.000     .6957388    .7768123
        3 6  |   .7301101   .0340544    21.44   0.000     .6633647    .7968555
        4 1  |   .1341854   .0453159     2.96   0.003     .0453678     .223003
        4 2  |   .1024602   .0233329     4.39   0.000     .0567285    .1481919
        4 3  |    .075906   .0102985     7.37   0.000     .0557214    .0960906
        4 4  |   .0546252   .0078661     6.94   0.000      .039208    .0700424
        4 5  |   .0382204   .0096899     3.94   0.000     .0192286    .0572123
        4 6  |   .0260012   .0101658     2.56   0.011     .0060766    .0459258
        5 1  |   .2629521   .0480915     5.47   0.000     .1686944    .3572098
        5 2  |   .2155353   .0282674     7.62   0.000     .1601322    .2709383
        5 3  |    .171408   .0148061    11.58   0.000     .1423887    .2004273
        5 4  |   .1324159   .0109237    12.12   0.000     .1110059    .1538259
        5 5  |   .0994567   .0133799     7.43   0.000     .0732326    .1256809
        5 6  |   .0726313   .0152293     4.77   0.000     .0427824    .1024802
------------------------------------------------------------------------------

. margins, atmeans at(christian=(0 1))

Adjusted predictions                            Number of obs     =      1,207
Model VCE    : Robust

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =    8.437662 (mean)
               christian       =           0

2._at        : gender          =    .5074661 (mean)
               newage          =    37.89459 (mean)
               religscale      =    8.437662 (mean)
               christian       =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0635558   .0078642     8.08   0.000     .0481423    .0789694
        1 2  |   .0388379   .0232405     1.67   0.095    -.0067126    .0843885
        2 1  |   .0219155   .0045503     4.82   0.000     .0129971    .0308338
        2 2  |   2.18e-08   4.51e-09     4.82   0.000     1.29e-08    3.06e-08
        3 1  |   .7170229   .0142932    50.17   0.000     .6890087    .7450372
        3 2  |   .5963109   .0597151     9.99   0.000     .4792714    .7133504
        4 1  |   .0582256   .0076585     7.60   0.000     .0432152     .073236
        4 2  |   .1402726   .0406939     3.45   0.001     .0605139    .2200312
        5 1  |   .1392801   .0108805    12.80   0.000     .1179547    .1606056
        5 2  |   .2245786   .0516415     4.35   0.000     .1233632     .325794
------------------------------------------------------------------------------

. mlogit tpartic4 gender newage  religscale if country==10 [pw=WT], rrr b(2)

Iteration 0:   log pseudolikelihood = -1029.9264  
Iteration 1:   log pseudolikelihood = -960.65476  
Iteration 2:   log pseudolikelihood = -953.95135  
Iteration 3:   log pseudolikelihood = -953.90587  
Iteration 4:   log pseudolikelihood = -953.90585  

Multinomial logistic regression                 Number of obs     =      1,154
                                                Wald chi2(9)      =     114.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -953.90585               Pseudo R2         =     0.0738

------------------------------------------------------------------------------------
                   |               Robust
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
            gender |   5.912811     1.2345     8.51   0.000     3.927144    8.902484
            newage |   .9545834   .0070129    -6.33   0.000     .9409368    .9684279
        religscale |   1.068971   .0281114     2.54   0.011     1.015269    1.125513
             _cons |   .2517243   .0775138    -4.48   0.000     .1376619    .4602954
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
            gender |   .8699838   .1700151    -0.71   0.476     .5931528    1.276015
            newage |   .9970193   .0061606    -0.48   0.629     .9850176    1.009167
        religscale |   .9321919   .0276631    -2.37   0.018     .8795198    .9880184
             _cons |   .2892598   .0832926    -4.31   0.000     .1645068    .5086187
-------------------+----------------------------------------------------------------
Oppose             |
            gender |   2.542877   .8968518     2.65   0.008     1.273837    5.076181
            newage |   .9629738   .0151869    -2.39   0.017     .9336634    .9932044
        religscale |   1.054082   .0425569     1.30   0.192     .9738869    1.140881
             _cons |   .0865768   .0445868    -4.75   0.000     .0315526    .2375569
------------------------------------------------------------------------------------

. margins, atmeans at(religscale=(0 3 6 9 12 15))

Adjusted predictions                            Number of obs     =      1,154
Model VCE    : Robust

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))

1._at        : gender          =    .4959693 (mean)
               newage          =    39.67621 (mean)
               religscale      =           0

2._at        : gender          =    .4959693 (mean)
               newage          =    39.67621 (mean)
               religscale      =           3

3._at        : gender          =    .4959693 (mean)
               newage          =    39.67621 (mean)
               religscale      =           6

4._at        : gender          =    .4959693 (mean)
               newage          =    39.67621 (mean)
               religscale      =           9

5._at        : gender          =    .4959693 (mean)
               newage          =    39.67621 (mean)
               religscale      =          12

6._at        : gender          =    .4959693 (mean)
               newage          =    39.67621 (mean)
               religscale      =          15

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |    .070328   .0137495     5.11   0.000     .0433796    .0972765
        1 2  |   .0871169   .0118556     7.35   0.000     .0638804    .1103533
        1 3  |   .1067881   .0106375    10.04   0.000      .085939    .1276372
        1 4  |   .1295643   .0136724     9.48   0.000     .1027668    .1563617
        1 5  |   .1556105   .0223575     6.96   0.000     .1117905    .1994304
        1 6  |   .1850077   .0354253     5.22   0.000     .1155754    .2544399
        2 1  |   .7316888    .028766    25.44   0.000     .6753085    .7880691
        2 2  |   .7419974   .0182553    40.65   0.000     .7062176    .7777772
        2 3  |    .744604   .0142667    52.19   0.000     .7166418    .7725661
        2 4  |   .7395883    .017927    41.26   0.000      .704452    .7747246
        2 5  |   .7271866   .0268312    27.10   0.000     .6745985    .7797748
        2 6  |   .7077814   .0394105    17.96   0.000     .6305382    .7850246
        3 1  |   .1754594   .0265985     6.60   0.000     .1233272    .2275915
        3 2  |   .1441347    .014494     9.94   0.000      .115727    .1725423
        3 3  |   .1171676   .0100186    11.70   0.000     .0975315    .1368036
        3 4  |   .0942732   .0122115     7.72   0.000      .070339    .1182073
        3 5  |   .0750862   .0150576     4.99   0.000     .0455738    .1045985
        3 6  |    .059201   .0166306     3.56   0.000     .0266057    .0917963
        4 1  |   .0225238   .0075879     2.97   0.003     .0076518    .0373958
        4 2  |   .0267511    .006637     4.03   0.000     .0137429    .0397593
        4 3  |   .0314404   .0060975     5.16   0.000     .0194894    .0433913
        4 4  |   .0365742   .0073771     4.96   0.000     .0221153    .0510332
        4 5  |   .0421167   .0111246     3.79   0.000     .0203128    .0639206
        4 6  |   .0480099   .0168962     2.84   0.004     .0148941    .0811258
------------------------------------------------------------------------------

. 
. * =====================================
. * TRUSTS MUSLIM BROTHERHOOD OR ENNAHDA
. * =====================================
. clear

. use fullarabbarom2.dta

. tab q20112 egpartic5 if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

     Trust the Muslim |
   Brotherhood (Egypt |          Egypt: Part/Aid/Support/Apath/Oppose
                only) | Participa        Aid    Support  Apathetic     Oppose |     Total
----------------------+-------------------------------------------------------+----------
          Unspecified |         0          0          2          2          0 |         4 
                      |      0.00       0.00       0.24       2.44       0.00 |      0.33 
----------------------+-------------------------------------------------------+----------
I trust it to a great |        21          7        161         18         36 |       243 
                      |     23.33      25.00      19.30      21.95      20.34 |     20.07 
----------------------+-------------------------------------------------------+----------
I trust it to a mediu |        22          6        199         14         43 |       284 
                      |     24.44      21.43      23.86      17.07      24.29 |     23.45 
----------------------+-------------------------------------------------------+----------
I trust it to a limit |        10          1        152         20         21 |       204 
                      |     11.11       3.57      18.23      24.39      11.86 |     16.85 
----------------------+-------------------------------------------------------+----------
I absolutely do not t |        32         11        256         22         62 |       383 
                      |     35.56      39.29      30.70      26.83      35.03 |     31.63 
----------------------+-------------------------------------------------------+----------
         I don�t know |         4          3         63          6         15 |        91 
                      |      4.44      10.71       7.55       7.32       8.47 |      7.51 
----------------------+-------------------------------------------------------+----------
   Declined to answer |         1          0          1          0          0 |         2 
                      |      1.11       0.00       0.12       0.00       0.00 |      0.17 
----------------------+-------------------------------------------------------+----------
                Total |        90         28        834         82        177 |     1,211 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab q20114 tpartic4 if country==10, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

To what degree do you |
 currently trust: the |    Tunisia: Part/Supp/Apath,Inact/Oppose
Nahda party/movement? | Participa    Support  Apathetic     Oppose |     Total
----------------------+--------------------------------------------+----------
          Unspecified |         1          2          0          0 |         3 
                      |      0.58       0.25       0.00       0.00 |      0.26 
----------------------+--------------------------------------------+----------
I trust it to a great |        37        150         18          4 |       209 
                      |     21.64      18.47      13.64      10.26 |     18.11 
----------------------+--------------------------------------------+----------
I trust it to a mediu |        41        171         31          7 |       250 
                      |     23.98      21.06      23.48      17.95 |     21.66 
----------------------+--------------------------------------------+----------
I trust it to a limit |        23         94         13          4 |       134 
                      |     13.45      11.58       9.85      10.26 |     11.61 
----------------------+--------------------------------------------+----------
I absolutely do not t |        55        229         38         20 |       342 
                      |     32.16      28.20      28.79      51.28 |     29.64 
----------------------+--------------------------------------------+----------
         I don�t know |        13        160         32          4 |       209 
                      |      7.60      19.70      24.24      10.26 |     18.11 
----------------------+--------------------------------------------+----------
   Declined to answer |         1          6          0          0 |         7 
                      |      0.58       0.74       0.00       0.00 |      0.61 
----------------------+--------------------------------------------+----------
                Total |       171        812        132         39 |     1,154 
                      |    100.00     100.00     100.00     100.00 |    100.00 


. 
. * =============================================================================
. * BLOC RECRUITMENT IN ORANGE REV--VOTE OF PARTICIPANT INFLUENCED BY POLITICIAN
. * =============================================================================
. clear

. use monitoring20052014engmerged.dta

. tab EVA307_1 partic5a if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Vote for |
Yushchenko |
    in 3rd |
     round |
influenced |
        by |
endorsemen |
 t of:  A. |           Part/Aid/Support/Apathetic/Oppose
    Kinakh | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |       241         51        594        154        603 |     1,643 
           |     86.38      87.93      91.24     100.00      99.67 |     94.05 
-----------+-------------------------------------------------------+----------
       yes |        38          7         57          0          2 |       104 
           |     13.62      12.07       8.76       0.00       0.33 |      5.95 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        154        605 |     1,747 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA307_2 partic5a if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Vote for |
Yushchenko |
    in 3rd |
     round |
influenced |
        by |
endorsemen |
 t of:  A. |           Part/Aid/Support/Apathetic/Oppose
     Moroz | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |       233         45        541        154        604 |     1,577 
           |     83.51      77.59      83.10     100.00      99.83 |     90.27 
-----------+-------------------------------------------------------+----------
       yes |        46         13        110          0          1 |       170 
           |     16.49      22.41      16.90       0.00       0.17 |      9.73 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        154        605 |     1,747 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA307_3 partic5a if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Vote for |
Yushchenko |
    in 3rd |
     round |
influenced |
        by |
endorsemen |
t of:  Yu. |           Part/Aid/Support/Apathetic/Oppose
Timoshenko | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
-----------+-------------------------------------------------------+----------
        no |       179         38        500        153        600 |     1,470 
           |     64.16      65.52      76.80      99.35      99.17 |     84.14 
-----------+-------------------------------------------------------+----------
       yes |       100         20        151          1          5 |       277 
           |     35.84      34.48      23.20       0.65       0.83 |     15.86 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        154        605 |     1,747 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. 
. * ==================================================================
. * DATA FOR FIGURE 7.11: POL SELF-ID AMONG PARTICIPANTS, SUPPORTERS, 
. *   OPPONENTS (UKRAINE ONLY)
. * ==================================================================
. * Note:  Herfindahl indices calculated by hand
. clear

. use monitoring20052014engmerged.dta

. tab EVA13 partic5a if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Choose the political |
  tendency closest to |           Part/Aid/Support/Apathetic/Oppose
                  you | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
----------------------+-------------------------------------------------------+----------
            Communist |         3          1         32          9         82 |       127 
                      |      1.08       1.72       4.92       5.84      13.55 |      7.27 
----------------------+-------------------------------------------------------+----------
            Socialist |        37          7         88          8         86 |       226 
                      |     13.26      12.07      13.52       5.19      14.21 |     12.94 
----------------------+-------------------------------------------------------+----------
    Social-democratic |        31          6         75         17        114 |       243 
                      |     11.11      10.34      11.52      11.04      18.84 |     13.91 
----------------------+-------------------------------------------------------+----------
                Green |        10          2         14          3         20 |        49 
                      |      3.58       3.45       2.15       1.95       3.31 |      2.80 
----------------------+-------------------------------------------------------+----------
              Liberal |         3          1          8          3          6 |        21 
                      |      1.08       1.72       1.23       1.95       0.99 |      1.20 
----------------------+-------------------------------------------------------+----------
 Christian-democratic |        15          4         17          6         14 |        56 
                      |      5.38       6.90       2.61       3.90       2.31 |      3.21 
----------------------+-------------------------------------------------------+----------
  National-democratic |        78         13         72          5         13 |       181 
                      |     27.96      22.41      11.06       3.25       2.15 |     10.36 
----------------------+-------------------------------------------------------+----------
          Nationalist |        19          4         12          0          1 |        36 
                      |      6.81       6.90       1.84       0.00       0.17 |      2.06 
----------------------+-------------------------------------------------------+----------
                Other |        10          3          8          3          6 |        30 
                      |      3.58       5.17       1.23       1.95       0.99 |      1.72 
----------------------+-------------------------------------------------------+----------
      None in general |        19          2         73         23         58 |       175 
                      |      6.81       3.45      11.21      14.94       9.59 |     10.02 
----------------------+-------------------------------------------------------+----------
I have not yet define |        27          6        110         30         91 |       264 
                      |      9.68      10.34      16.90      19.48      15.04 |     15.11 
----------------------+-------------------------------------------------------+----------
I don't follow these  |        27          9        142         47        114 |       339 
                      |      9.68      15.52      21.81      30.52      18.84 |     19.40 
----------------------+-------------------------------------------------------+----------
                Total |       279         58        651        154        605 |     1,747 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA13 partic5a if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Choose the political |
  tendency closest to |           Part/Aid/Support/Apathetic/Oppose
                  you | Part in r    Aid rev  Support r  Apathetic  Oppose re |     Total
----------------------+-------------------------------------------------------+----------
            Communist |         0          2         12         11         47 |        72 
                      |      0.00       1.48       1.66       4.82       9.02 |      4.11 
----------------------+-------------------------------------------------------+----------
            Socialist |         0          2         45         21         95 |       163 
                      |      0.00       1.48       6.22       9.21      18.23 |      9.31 
----------------------+-------------------------------------------------------+----------
    Social-democratic |         8         11         75         24         54 |       172 
                      |      5.59       8.15      10.37      10.53      10.36 |      9.83 
----------------------+-------------------------------------------------------+----------
                Green |         3          1         15          5          9 |        33 
                      |      2.10       0.74       2.07       2.19       1.73 |      1.89 
----------------------+-------------------------------------------------------+----------
              Liberal |         9          8         19          4          5 |        45 
                      |      6.29       5.93       2.63       1.75       0.96 |      2.57 
----------------------+-------------------------------------------------------+----------
 Christian-democratic |        11          3         30          8         10 |        62 
                      |      7.69       2.22       4.15       3.51       1.92 |      3.54 
----------------------+-------------------------------------------------------+----------
  National-democratic |        45         49        129         11         14 |       248 
                      |     31.47      36.30      17.84       4.82       2.69 |     14.17 
----------------------+-------------------------------------------------------+----------
          Nationalist |        27         14         35          5          4 |        85 
                      |     18.88      10.37       4.84       2.19       0.77 |      4.86 
----------------------+-------------------------------------------------------+----------
                Other |         2          2          7          1          1 |        13 
                      |      1.40       1.48       0.97       0.44       0.19 |      0.74 
----------------------+-------------------------------------------------------+----------
      None in general |         7         12         74         33         74 |       200 
                      |      4.90       8.89      10.24      14.47      14.20 |     11.43 
----------------------+-------------------------------------------------------+----------
I have not yet define |        17         19        113         38         62 |       249 
                      |     11.89      14.07      15.63      16.67      11.90 |     14.23 
----------------------+-------------------------------------------------------+----------
I don't follow these  |        14         12        169         67        146 |       408 
                      |      9.79       8.89      23.37      29.39      28.02 |     23.31 
----------------------+-------------------------------------------------------+----------
                Total |       143        135        723        228        521 |     1,750 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. 
. * ==========================================================
. * REASONS PARTICIPANTS GAVE FOR PARTICIPATION--TUNISIAN AND 
. *   EGYPTIAN REVOLUTIONS
. * ==========================================================
. clear

. use fullarabbarom2.dta

. tab eg8091 egpartic5 if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

    What was the most |
 important reason for |
      the Jan25-Feb11 |          Egypt: Part/Aid/Support/Apath/Oppose
            protests? | Participa        Aid    Support  Apathetic     Oppose |     Total
----------------------+-------------------------------------------------------+----------
          Unspecified |         1          0          1          0          1 |         3 
                      |      1.11       0.00       0.12       0.00       0.56 |      0.25 
----------------------+-------------------------------------------------------+----------
Demands for improving |        33         12        454         45         99 |       643 
                      |     36.67      42.86      54.44      54.88      55.93 |     53.10 
----------------------+-------------------------------------------------------+----------
Demands for civil and |        16          2         49          4         11 |        82 
                      |     17.78       7.14       5.88       4.88       6.21 |      6.77 
----------------------+-------------------------------------------------------+----------
Demands for authority |        20          8         49          2         15 |        94 
                      |     22.22      28.57       5.88       2.44       8.47 |      7.76 
----------------------+-------------------------------------------------------+----------
 Combating corruption |        15          5        257         27         46 |       350 
                      |     16.67      17.86      30.82      32.93      25.99 |     28.90 
----------------------+-------------------------------------------------------+----------
Replacing the Mubarak |         2          1         10          1          3 |        17 
                      |      2.22       3.57       1.20       1.22       1.69 |      1.40 
----------------------+-------------------------------------------------------+----------
Objecting to pro-West |         0          0          1          0          0 |         1 
                      |      0.00       0.00       0.12       0.00       0.00 |      0.08 
----------------------+-------------------------------------------------------+----------
Objecting to pro-Isra |         2          0          0          0          0 |         2 
                      |      2.22       0.00       0.00       0.00       0.00 |      0.17 
----------------------+-------------------------------------------------------+----------
Social justices (just |         1          0          0          0          0 |         1 
                      |      1.11       0.00       0.00       0.00       0.00 |      0.08 
----------------------+-------------------------------------------------------+----------
Combating price hikes |         0          0          1          0          0 |         1 
                      |      0.00       0.00       0.12       0.00       0.00 |      0.08 
----------------------+-------------------------------------------------------+----------
           No answer  |         0          0          1          0          0 |         1 
                      |      0.00       0.00       0.12       0.00       0.00 |      0.08 
----------------------+-------------------------------------------------------+----------
        I don�t know  |         0          0         11          3          2 |        16 
                      |      0.00       0.00       1.32       3.66       1.13 |      1.32 
----------------------+-------------------------------------------------------+----------
                Total |        90         28        834         82        177 |     1,211 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab eg8092 egpartic5 if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  What was the second |
most important reason |
  for the Jan25-Feb11 |          Egypt: Part/Aid/Support/Apath/Oppose
            protests? | Participa        Aid    Support  Apathetic     Oppose |     Total
----------------------+-------------------------------------------------------+----------
          Unspecified |         1          0          1          0          1 |         3 
                      |      1.11       0.00       0.12       0.00       0.56 |      0.25 
----------------------+-------------------------------------------------------+----------
Demands for improving |        26         10        225         22         42 |       325 
                      |     28.89      35.71      26.98      26.83      23.73 |     26.84 
----------------------+-------------------------------------------------------+----------
Demands for civil and |        10          4         75          5         24 |       118 
                      |     11.11      14.29       8.99       6.10      13.56 |      9.74 
----------------------+-------------------------------------------------------+----------
Demands for authority |        13          4        106         15         28 |       166 
                      |     14.44      14.29      12.71      18.29      15.82 |     13.71 
----------------------+-------------------------------------------------------+----------
 Combating corruption |        36          9        379         35         71 |       530 
                      |     40.00      32.14      45.44      42.68      40.11 |     43.77 
----------------------+-------------------------------------------------------+----------
Replacing the Mubarak |         3          1         26          1          7 |        38 
                      |      3.33       3.57       3.12       1.22       3.95 |      3.14 
----------------------+-------------------------------------------------------+----------
Objecting to pro-West |         0          0          2          0          0 |         2 
                      |      0.00       0.00       0.24       0.00       0.00 |      0.17 
----------------------+-------------------------------------------------------+----------
Objecting to pro-Isra |         1          0          3          0          2 |         6 
                      |      1.11       0.00       0.36       0.00       1.13 |      0.50 
----------------------+-------------------------------------------------------+----------
Social justices (just |         0          0          1          1          0 |         2 
                      |      0.00       0.00       0.12       1.22       0.00 |      0.17 
----------------------+-------------------------------------------------------+----------
Combating price hikes |         0          0          2          0          0 |         2 
                      |      0.00       0.00       0.24       0.00       0.00 |      0.17 
----------------------+-------------------------------------------------------+----------
Combating unemploymen |         0          0          2          0          0 |         2 
                      |      0.00       0.00       0.24       0.00       0.00 |      0.17 
----------------------+-------------------------------------------------------+----------
           No answer  |         0          0          1          0          0 |         1 
                      |      0.00       0.00       0.12       0.00       0.00 |      0.08 
----------------------+-------------------------------------------------------+----------
        I don�t know  |         0          0         11          3          2 |        16 
                      |      0.00       0.00       1.32       3.66       1.13 |      1.32 
----------------------+-------------------------------------------------------+----------
                Total |        90         28        834         82        177 |     1,211 
                      |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab t9091 tpartic4 if country==10, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Most important reason |
        some citizens |
  participated in the |
      Dec2010-Jan2011 |    Tunisia: Part/Supp/Apath,Inact/Oppose
              revoln: | Participa    Support  Apathetic     Oppose |     Total
----------------------+--------------------------------------------+----------
Demands for improving |        99        500         93         24 |       716 
                      |     57.89      61.58      70.45      61.54 |     62.05 
----------------------+--------------------------------------------+----------
Demands for civil and |        34        110         12          9 |       165 
                      |     19.88      13.55       9.09      23.08 |     14.30 
----------------------+--------------------------------------------+----------
 Combating corruption |        26        154         17          4 |       201 
                      |     15.20      18.97      12.88      10.26 |     17.42 
----------------------+--------------------------------------------+----------
Replacing the Ben Ali |        11         31          5          0 |        47 
                      |      6.43       3.82       3.79       0.00 |      4.07 
----------------------+--------------------------------------------+----------
Objecting to pro-West |         0          0          1          0 |         1 
                      |      0.00       0.00       0.76       0.00 |      0.09 
----------------------+--------------------------------------------+----------
         I don�t know |         1         16          4          2 |        23 
                      |      0.58       1.97       3.03       5.13 |      1.99 
----------------------+--------------------------------------------+----------
   Declined to answer |         0          1          0          0 |         1 
                      |      0.00       0.12       0.00       0.00 |      0.09 
----------------------+--------------------------------------------+----------
                Total |       171        812        132         39 |     1,154 
                      |    100.00     100.00     100.00     100.00 |    100.00 


. tab t9092 tpartic4 if country==10, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

   2nd most important |
 reason some citizens |
      participated in |
      Dec2010-Jan2011 |    Tunisia: Part/Supp/Apath,Inact/Oppose
              revoln: | Participa    Support  Apathetic     Oppose |     Total
----------------------+--------------------------------------------+----------
Demands for improving |        32        151         20          8 |       211 
                      |     18.82      18.92      15.38      21.62 |     18.59 
----------------------+--------------------------------------------+----------
Demands for civil and |        53        239         38          7 |       337 
                      |     31.18      29.95      29.23      18.92 |     29.69 
----------------------+--------------------------------------------+----------
 Combating corruption |        76        359         63         18 |       516 
                      |     44.71      44.99      48.46      48.65 |     45.46 
----------------------+--------------------------------------------+----------
Replacing the Ben Ali |         7         36          7          3 |        53 
                      |      4.12       4.51       5.38       8.11 |      4.67 
----------------------+--------------------------------------------+----------
Objecting to pro-West |         2         10          0          1 |        13 
                      |      1.18       1.25       0.00       2.70 |      1.15 
----------------------+--------------------------------------------+----------
         I don�t know |         0          3          2          0 |         5 
                      |      0.00       0.38       1.54       0.00 |      0.44 
----------------------+--------------------------------------------+----------
                Total |       170        798        130         37 |     1,135 
                      |    100.00     100.00     100.00     100.00 |    100.00 


. 
. * ===========================================================================
. * REASONS PARTICIPANTS GAVE FOR PARTICIPATION--UKRAINE:  KIIS AND MONITORING
. * ===========================================================================
. clear

. use mohyla.orangerev.dta

. tab v22_1 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
   against |
falsificat |
    ion of |           Protest & vote intention crosstab
 elections | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |        92        250        210        648         79 |     1,279 
           |     33.21      45.45      78.07      88.89      96.34 |     67.07 
-----------+-------------------------------------------------------+----------
       yes |       185        300         59         81          3 |       628 
           |     66.79      54.55      21.93      11.11       3.66 |     32.93 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_2 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
   support |           Protest & vote intention crosstab
Yushchenko | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       191        387        230        646         76 |     1,530 
           |     68.95      70.36      85.50      88.61      92.68 |     80.23 
-----------+-------------------------------------------------------+----------
       yes |        86        163         39         83          6 |       377 
           |     31.05      29.64      14.50      11.39       7.32 |     19.77 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_3 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
   support |           Protest & vote intention crosstab
Yanukovych | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       274        544        254        573         47 |     1,692 
           |     98.92      98.91      94.42      78.60      57.32 |     88.73 
-----------+-------------------------------------------------------+----------
       yes |         3          6         15        156         35 |       215 
           |      1.08       1.09       5.58      21.40      42.68 |     11.27 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_4 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
to express |
  attitude |
    toward |
authoritie |           Protest & vote intention crosstab
         s | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       205        377        211        607         68 |     1,468 
           |     74.01      68.55      78.44      83.26      82.93 |     76.98 
-----------+-------------------------------------------------------+----------
       yes |        72        173         58        122         14 |       439 
           |     25.99      31.45      21.56      16.74      17.07 |     23.02 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_5 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
  to stand |
for values |
of a just, |
democratic |           Protest & vote intention crosstab
   society | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       166        357        228        667         70 |     1,488 
           |     59.93      64.91      84.76      91.50      85.37 |     78.03 
-----------+-------------------------------------------------------+----------
       yes |       111        193         41         62         12 |       419 
           |     40.07      35.09      15.24       8.50      14.63 |     21.97 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_6 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
   to feel |
 happy, to |
experience |           Protest & vote intention crosstab
solidarity | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       267        541        249        665         73 |     1,795 
           |     96.39      98.36      92.57      91.22      89.02 |     94.13 
-----------+-------------------------------------------------------+----------
       yes |        10          9         20         64          9 |       112 
           |      3.61       1.64       7.43       8.78      10.98 |      5.87 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_7 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
to be with |
   friends |
       and |
acquaintan |           Protest & vote intention crosstab
       ces | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       274        540        252        656         78 |     1,800 
           |     98.92      98.18      93.68      89.99      95.12 |     94.39 
-----------+-------------------------------------------------------+----------
       yes |         3         10         17         73          4 |       107 
           |      1.08       1.82       6.32      10.01       4.88 |      5.61 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_8 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
 forced to |
  by their |           Protest & vote intention crosstab
    bosses | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       275        545        262        667         74 |     1,823 
           |     99.28      99.09      97.40      91.50      90.24 |     95.60 
-----------+-------------------------------------------------------+----------
       yes |         2          5          7         62          8 |        84 
           |      0.72       0.91       2.60       8.50       9.76 |      4.40 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_9 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
  they are |           Protest & vote intention crosstab
paid money | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       273        530        192        405         51 |     1,451 
           |     98.56      96.36      71.38      55.56      62.20 |     76.09 
-----------+-------------------------------------------------------+----------
       yes |         4         20         77        324         31 |       456 
           |      1.44       3.64      28.62      44.44      37.80 |     23.91 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_10 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |           Protest & vote intention crosstab
     other | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       275        535        263        718         75 |     1,866 
           |     99.28      97.27      97.77      98.49      91.46 |     97.85 
-----------+-------------------------------------------------------+----------
       yes |         2         15          6         11          7 |        41 
           |      0.72       2.73       2.23       1.51       8.54 |      2.15 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab v22_11 demopartvote, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Why |
 protest?: |
   hard to |           Protest & vote intention crosstab
       say | Orange de  Orange vo  No vote,   Blue vote  Blue demo |     Total
-----------+-------------------------------------------------------+----------
        no |       276        527        224        681         82 |     1,790 
           |     99.64      95.82      83.27      93.42     100.00 |     93.86 
-----------+-------------------------------------------------------+----------
       yes |         1         23         45         48          0 |       117 
           |      0.36       4.18      16.73       6.58       0.00 |      6.14 
-----------+-------------------------------------------------------+----------
     Total |       277        550        269        729         82 |     1,907 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. clear

. use monitoring20052014engmerged.dta

. tab EVA317_1 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
   protest |
   against |
authoritie |            Part/Aid/Support/Oppose/Counter
         s |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       124         20        319        404         28 |       895 
           |     44.44      34.48      49.00      71.25      73.68 |     56.18 
-----------+-------------------------------------------------------+----------
       yes |       155         38        332        163         10 |       698 
           |     55.56      65.52      51.00      28.75      26.32 |     43.82 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_2 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
   hope to |
   improve |
  material |            Part/Aid/Support/Oppose/Counter
      cond |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       169         38        408        448         25 |     1,088 
           |     60.57      65.52      62.67      79.01      65.79 |     68.30 
-----------+-------------------------------------------------------+----------
       yes |       110         20        243        119         13 |       505 
           |     39.43      34.48      37.33      20.99      34.21 |     31.70 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_3 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
dislike of |
    one of |            Part/Aid/Support/Oppose/Counter
candidates |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       189         47        520        415         22 |     1,193 
           |     67.74      81.03      79.88      73.19      57.89 |     74.89 
-----------+-------------------------------------------------------+----------
       yes |        90         11        131        152         16 |       400 
           |     32.26      18.97      20.12      26.81      42.11 |     25.11 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_4 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
 awakening |
    of Ukr |
  national |
consciousn |            Part/Aid/Support/Oppose/Counter
       ess |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       164         37        504        534         34 |     1,273 
           |     58.78      63.79      77.42      94.18      89.47 |     79.91 
-----------+-------------------------------------------------------+----------
       yes |       115         21        147         33          4 |       320 
           |     41.22      36.21      22.58       5.82      10.53 |     20.09 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_5 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
   protest |
   against |            Part/Aid/Support/Oppose/Counter
 injustice |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       185         44        499        505         32 |     1,265 
           |     66.31      75.86      76.65      89.07      84.21 |     79.41 
-----------+-------------------------------------------------------+----------
       yes |        94         14        152         62          6 |       328 
           |     33.69      24.14      23.35      10.93      15.79 |     20.59 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_6 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
   wish to |
participat |
    e in a |
  colorful |            Part/Aid/Support/Oppose/Counter
 spectacle |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       276         56        640        434         29 |     1,435 
           |     98.92      96.55      98.31      76.54      76.32 |     90.08 
-----------+-------------------------------------------------------+----------
       yes |         3          2         11        133          9 |       158 
           |      1.08       3.45       1.69      23.46      23.68 |      9.92 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_7 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
   concern |
for future |
        of |            Part/Aid/Support/Oppose/Counter
  children |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       183         45        438        527         32 |     1,225 
           |     65.59      77.59      67.28      92.95      84.21 |     76.90 
-----------+-------------------------------------------------------+----------
       yes |        96         13        213         40          6 |       368 
           |     34.41      22.41      32.72       7.05      15.79 |     23.10 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_8 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
    choice |
   between |
  good and |            Part/Aid/Support/Oppose/Counter
      evil |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       220         44        529        541         34 |     1,368 
           |     78.85      75.86      81.26      95.41      89.47 |     85.88 
-----------+-------------------------------------------------------+----------
       yes |        59         14        122         26          4 |       225 
           |     21.15      24.14      18.74       4.59      10.53 |     14.12 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_9 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
    geopol |
    choice |
   between |
  West and |            Part/Aid/Support/Oppose/Counter
    Russia |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       269         57        644        505         36 |     1,511 
           |     96.42      98.28      98.92      89.07      94.74 |     94.85 
-----------+-------------------------------------------------------+----------
       yes |        10          1          7         62          2 |        82 
           |      3.58       1.72       1.08      10.93       5.26 |      5.15 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_10 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |            Part/Aid/Support/Oppose/Counter
     other |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       277         58        650        540         33 |     1,558 
           |     99.28     100.00      99.85      95.24      86.84 |     97.80 
-----------+-------------------------------------------------------+----------
       yes |         2          0          1         27          5 |        35 
           |      0.72       0.00       0.15       4.76      13.16 |      2.20 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. tab EVA317_11 partic5 if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Reason for |
  protest: |
   hard to |            Part/Aid/Support/Oppose/Counter
       say |      Part        Aid    Support     Oppose    Counter |     Total
-----------+-------------------------------------------------------+----------
        no |       277         57        593        425         32 |     1,384 
           |     99.28      98.28      91.09      74.96      84.21 |     86.88 
-----------+-------------------------------------------------------+----------
       yes |         2          1         58        142          6 |       209 
           |      0.72       1.72       8.91      25.04      15.79 |     13.12 
-----------+-------------------------------------------------------+----------
     Total |       279         58        651        567         38 |     1,593 
           |    100.00     100.00     100.00     100.00     100.00 |    100.00 


. 
. * ================================================
. * FIGURE 7.12:  CLUSTER PROFILES OF PARTICIPANTS
. * ================================================
. * Figure 7.12 calculated using Latent Gold 4.5.0--separate analysis
. 
. * ========================================================
. * ATTITUDES TOWARD DEMOCRACY AMONG PARTICIPANTS:  UKRAINE
. * ========================================================
. clear

. use monitoring20052014engmerged.dta

. * Leaders vs. laws
. tab leadersvslaws newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

     Strong |
    leaders |  Participated in rev
       over |   protests vs. all
laws/discus |   other respondents
      sions |         0          1 |     Total
------------+----------------------+----------
   Disagree |       335         62 |       397 
            |     22.07      22.14 |     22.08 
------------+----------------------+----------
Hard to say |       294         34 |       328 
            |     19.37      12.14 |     18.24 
------------+----------------------+----------
      Agree |       889        184 |     1,073 
            |     58.56      65.71 |     59.68 
------------+----------------------+----------
      Total |     1,518        280 |     1,798 
            |    100.00     100.00 |    100.00 


. tab leadersvslaws newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

     Strong |
    leaders |  Participated in rev
       over |   protests vs. all
laws/discus |   other respondents
      sions |         0          1 |     Total
------------+----------------------+----------
   Disagree |       328         44 |       372 
            |     20.01      28.39 |     20.74 
------------+----------------------+----------
Hard to say |       275         13 |       288 
            |     16.78       8.39 |     16.05 
------------+----------------------+----------
      Agree |     1,036         98 |     1,134 
            |     63.21      63.23 |     63.21 
------------+----------------------+----------
      Total |     1,639        155 |     1,794 
            |    100.00     100.00 |    100.00 


. * Ukraine needs a multi-party system
. tab multiparty newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

     Favors |  Participated in rev
 multiparty |   protests vs. all
  system in |   other respondents
    Ukraine |         0          1 |     Total
------------+----------------------+----------
         No |       529        114 |       643 
            |     35.06      40.71 |     35.94 
------------+----------------------+----------
Hard to say |       533         75 |       608 
            |     35.32      26.79 |     33.99 
------------+----------------------+----------
        Yes |       447         91 |       538 
            |     29.62      32.50 |     30.07 
------------+----------------------+----------
      Total |     1,509        280 |     1,789 
            |    100.00     100.00 |    100.00 


. tab multiparty newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

     Favors |  Participated in rev
 multiparty |   protests vs. all
  system in |   other respondents
    Ukraine |         0          1 |     Total
------------+----------------------+----------
         No |       707         32 |       739 
            |     43.19      20.92 |     41.28 
------------+----------------------+----------
Hard to say |       499         41 |       540 
            |     30.48      26.80 |     30.17 
------------+----------------------+----------
        Yes |       431         80 |       511 
            |     26.33      52.29 |     28.55 
------------+----------------------+----------
      Total |     1,637        153 |     1,790 
            |    100.00     100.00 |    100.00 


. * Gypsies as inhabitants of Ukraine
. tab EVA120_1 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
Gypsies to |  Participated in rev
       be: |   protests vs. all
members of |   other respondents
 my family |         0          1 |     Total
-----------+----------------------+----------
        no |     1,499        276 |     1,775 
           |     98.62      98.57 |     98.61 
-----------+----------------------+----------
       yes |        21          4 |        25 
           |      1.38       1.43 |      1.39 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120_2 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |  Participated in rev
Gypsies to |   protests vs. all
 be: close |   other respondents
   friends |         0          1 |     Total
-----------+----------------------+----------
        no |     1,502        277 |     1,779 
           |     98.82      98.93 |     98.83 
-----------+----------------------+----------
       yes |        18          3 |        21 
           |      1.18       1.07 |      1.17 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120_3 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |  Participated in rev
Gypsies to |   protests vs. all
       be: |   other respondents
 neighbors |         0          1 |     Total
-----------+----------------------+----------
        no |     1,474        277 |     1,751 
           |     96.97      98.93 |     97.28 
-----------+----------------------+----------
       yes |        46          3 |        49 
           |      3.03       1.07 |      2.72 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120_4 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
Gypsies to |  Participated in rev
       be: |   protests vs. all
colleagues |   other respondents
   at work |         0          1 |     Total
-----------+----------------------+----------
        no |     1,506        278 |     1,784 
           |     99.08      99.29 |     99.11 
-----------+----------------------+----------
       yes |        14          2 |        16 
           |      0.92       0.71 |      0.89 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120_5 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
Gypsies to |
       be: |  Participated in rev
inhabitant |   protests vs. all
      s of |   other respondents
   Ukraine |         0          1 |     Total
-----------+----------------------+----------
        no |     1,157        230 |     1,387 
           |     76.12      82.14 |     77.06 
-----------+----------------------+----------
       yes |       363         50 |       413 
           |     23.88      17.86 |     22.94 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120_6 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
Gypsies to |
       be: |
  visitors |  Participated in rev
        to |   protests vs. all
  Ukraine, |   other respondents
  tourists |         0          1 |     Total
-----------+----------------------+----------
        no |     1,093        194 |     1,287 
           |     71.91      69.29 |     71.50 
-----------+----------------------+----------
       yes |       427         86 |       513 
           |     28.09      30.71 |     28.50 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120_7 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
Gypsies to |
be: prefer |  Participated in rev
    not to |   protests vs. all
  allow in |   other respondents
   Ukraine |         0          1 |     Total
-----------+----------------------+----------
        no |       894        149 |     1,043 
           |     58.82      53.21 |     57.94 
-----------+----------------------+----------
       yes |       626        131 |       757 
           |     41.18      46.79 |     42.06 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA120 newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

                      |  Participated in rev
                      |   protests vs. all
    Prepared to allow |   other respondents
 Gypsies to be . . .  |         0          1 |     Total
----------------------+----------------------+----------
 Members of my family |         5          0 |         5 
                      |      0.31       0.00 |      0.28 
----------------------+----------------------+----------
        Close friends |        20          2 |        22 
                      |      1.22       1.32 |      1.23 
----------------------+----------------------+----------
            Neighbors |        40          5 |        45 
                      |      2.44       3.29 |      2.52 
----------------------+----------------------+----------
   Colleagues at work |        22          1 |        23 
                      |      1.34       0.66 |      1.29 
----------------------+----------------------+----------
Inhabitants of Ukrain |       376         49 |       425 
                      |     22.97      32.24 |     23.76 
----------------------+----------------------+----------
Visitors to Ukraine,  |       553         40 |       593 
                      |     33.78      26.32 |     33.15 
----------------------+----------------------+----------
Prefer not to allow i |       621         55 |       676 
                      |     37.94      36.18 |     37.79 
----------------------+----------------------+----------
                Total |     1,637        152 |     1,789 
                      |    100.00     100.00 |    100.00 


. * Jews as inhabitants of Ukraine
. tab EVA107_1 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
   Jews to |  Participated in rev
       be: |   protests vs. all
members of |   other respondents
 my family |         0          1 |     Total
-----------+----------------------+----------
        no |     1,468        275 |     1,743 
           |     96.58      98.21 |     96.83 
-----------+----------------------+----------
       yes |        52          5 |        57 
           |      3.42       1.79 |      3.17 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107_2 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |  Participated in rev
   Jews to |   protests vs. all
 be: close |   other respondents
   friends |         0          1 |     Total
-----------+----------------------+----------
        no |     1,409        267 |     1,676 
           |     92.70      95.36 |     93.11 
-----------+----------------------+----------
       yes |       111         13 |       124 
           |      7.30       4.64 |      6.89 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107_3 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |  Participated in rev
   Jews to |   protests vs. all
       be: |   other respondents
 neighbors |         0          1 |     Total
-----------+----------------------+----------
        no |     1,357        262 |     1,619 
           |     89.28      93.57 |     89.94 
-----------+----------------------+----------
       yes |       163         18 |       181 
           |     10.72       6.43 |     10.06 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107_4 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
   Jews to |  Participated in rev
       be: |   protests vs. all
colleagues |   other respondents
   at work |         0          1 |     Total
-----------+----------------------+----------
        no |     1,415        257 |     1,672 
           |     93.09      91.79 |     92.89 
-----------+----------------------+----------
       yes |       105         23 |       128 
           |      6.91       8.21 |      7.11 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107_5 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
   Jews to |
       be: |  Participated in rev
inhabitant |   protests vs. all
      s of |   other respondents
   Ukraine |         0          1 |     Total
-----------+----------------------+----------
        no |     1,135        216 |     1,351 
           |     74.67      77.14 |     75.06 
-----------+----------------------+----------
       yes |       385         64 |       449 
           |     25.33      22.86 |     24.94 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107_6 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
   Jews to |
       be: |
  visitors |  Participated in rev
        to |   protests vs. all
  Ukraine, |   other respondents
  tourists |         0          1 |     Total
-----------+----------------------+----------
        no |     1,004        165 |     1,169 
           |     66.05      58.93 |     64.94 
-----------+----------------------+----------
       yes |       516        115 |       631 
           |     33.95      41.07 |     35.06 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107_7 newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  Prepared |
  to allow |
   Jews to |
be: prefer |  Participated in rev
    not to |   protests vs. all
  allow in |   other respondents
   Ukraine |         0          1 |     Total
-----------+----------------------+----------
        no |     1,340        239 |     1,579 
           |     88.16      85.36 |     87.72 
-----------+----------------------+----------
       yes |       180         41 |       221 
           |     11.84      14.64 |     12.28 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab EVA107 newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

                      |  Participated in rev
                      |   protests vs. all
    Prepared to allow |   other respondents
    Jews to be . . .  |         0          1 |     Total
----------------------+----------------------+----------
 Members of my family |        46          2 |        48 
                      |      2.81       1.30 |      2.68 
----------------------+----------------------+----------
        Close friends |       141         21 |       162 
                      |      8.61      13.64 |      9.04 
----------------------+----------------------+----------
            Neighbors |       203         21 |       224 
                      |     12.39      13.64 |     12.50 
----------------------+----------------------+----------
   Colleagues at work |       104         13 |       117 
                      |      6.35       8.44 |      6.53 
----------------------+----------------------+----------
Inhabitants of Ukrain |       392         50 |       442 
                      |     23.93      32.47 |     24.67 
----------------------+----------------------+----------
Visitors to Ukraine,  |       643         36 |       679 
                      |     39.26      23.38 |     37.89 
----------------------+----------------------+----------
Prefer not to allow i |       109         11 |       120 
                      |      6.65       7.14 |      6.70 
----------------------+----------------------+----------
                Total |     1,638        154 |     1,792 
                      |    100.00     100.00 |    100.00 


. 
. * =========================================
. * MEMBERSHIP IN CIVIL SOCIETY ASSOCIATIONS
. * =========================================
. * Ukrainian revolutions
. clear

. use monitoring20052014engmerged.dta

. tab civsoc newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Belongs to |
     civil |  Participated in rev
   society |   protests vs. all
associatio |   other respondents
   n (0/1) |         0          1 |     Total
-----------+----------------------+----------
        no |     1,288        219 |     1,507 
           |     84.74      78.21 |     83.72 
-----------+----------------------+----------
       yes |       232         61 |       293 
           |     15.26      21.79 |     16.28 
-----------+----------------------+----------
     Total |     1,520        280 |     1,800 
           |    100.00     100.00 |    100.00 


. tab civsoc newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Belongs to |
     civil |  Participated in rev
   society |   protests vs. all
associatio |   other respondents
   n (0/1) |         0          1 |     Total
-----------+----------------------+----------
        no |     1,454        110 |     1,564 
           |     88.39      70.97 |     86.89 
-----------+----------------------+----------
       yes |       191         45 |       236 
           |     11.61      29.03 |     13.11 
-----------+----------------------+----------
     Total |     1,645        155 |     1,800 
           |    100.00     100.00 |    100.00 


. * Egyptian and Tunisian revolutions
. clear

. use fullarabbarom2.dta

. tab membany egrevpart if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Are you a |
 member of |
       any |
organizati |    Participated in
  on (from |  Egyptian rev (0/1)
    q501)? |         0          1 |     Total
-----------+----------------------+----------
     No/NA |       978         51 |     1,029 
           |     87.24      56.67 |     84.97 
-----------+----------------------+----------
       Yes |       143         39 |       182 
           |     12.76      43.33 |     15.03 
-----------+----------------------+----------
     Total |     1,121         90 |     1,211 
           |    100.00     100.00 |    100.00 


. tab membany trevpart if country==10, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Are you a |
 member of |
       any |
organizati |    Participated in
  on (from |  Tunisian rev (0/1)
    q501)? |         0          1 |     Total
-----------+----------------------+----------
     No/NA |       938        135 |     1,073 
           |     95.42      78.95 |     92.98 
-----------+----------------------+----------
       Yes |        45         36 |        81 
           |      4.58      21.05 |      7.02 
-----------+----------------------+----------
     Total |       983        171 |     1,154 
           |    100.00     100.00 |    100.00 


. 
. * ==============================================
. * GROWTH OF DIGITAL TECHNOLOGIES IN REVOLUTIONS
. * ==============================================
. clear

. use revolutionaryeps.dta

. * Urban civic vs. other revs since 1994
. logit socialmediaused startyear urbancivic if startyear>1993, or

Iteration 0:   log likelihood = -48.016568  
Iteration 1:   log likelihood = -37.911578  
Iteration 2:   log likelihood = -37.769873  
Iteration 3:   log likelihood = -37.769604  
Iteration 4:   log likelihood = -37.769604  

Logistic regression                             Number of obs     =         71
                                                LR chi2(2)        =      20.49
                                                Prob > chi2       =     0.0000
Log likelihood = -37.769604                     Pseudo R2         =     0.2134

---------------------------------------------------------------------------------
socialmediaused | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
      startyear |   1.146074   .0576668     2.71   0.007     1.038443     1.26486
     urbancivic |   6.260411   4.053673     2.83   0.005     1.759714    22.27222
          _cons |   1.4e-119   1.4e-117    -2.71   0.007     1.6e-205    1.17e-33
---------------------------------------------------------------------------------

. margins, atmeans at(urbancivic=(0 1))

Adjusted predictions                            Number of obs     =         71
Model VCE    : OIM

Expression   : Pr(socialmediaused), predict()

1._at        : startyear       =    2006.056 (mean)
               urbancivic      =           0

2._at        : startyear       =    2006.056 (mean)
               urbancivic      =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .4545793   .0809385     5.62   0.000     .2959428    .6132158
          2  |   .8391694   .0753863    11.13   0.000      .691415    .9869238
------------------------------------------------------------------------------

. * Media use in urban civic revs since 1994
. tab newspaperused urbancivic if startyear<1994, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
    use of |
     print |
  material |
(newspaper |
        s, |
pamphlets, |  Urban civic episode
 leaflets? |        no        yes |     Total
-----------+----------------------+----------
        no |        84          3 |        87 
           |     34.15      10.71 |     31.75 
-----------+----------------------+----------
       yes |       162         25 |       187 
           |     65.85      89.29 |     68.25 
-----------+----------------------+----------
     Total |       246         28 |       274 
           |    100.00     100.00 |    100.00 


. tab radioused urbancivic if startyear<1994, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
    use of |  Urban civic episode
    radio? |        no        yes |     Total
-----------+----------------------+----------
        no |       151         14 |       165 
           |     61.38      50.00 |     60.22 
-----------+----------------------+----------
       yes |        95         14 |       109 
           |     38.62      50.00 |     39.78 
-----------+----------------------+----------
     Total |       246         28 |       274 
           |    100.00     100.00 |    100.00 


. tab televisused urbancivic if startyear<1994, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
    use of |
television |
       (or |
attempt to |
      gain |
   control |  Urban civic episode
      of)? |        no        yes |     Total
-----------+----------------------+----------
        no |       233         18 |       251 
           |     94.72      64.29 |     91.61 
-----------+----------------------+----------
       yes |        13         10 |        23 
           |      5.28      35.71 |      8.39 
-----------+----------------------+----------
     Total |       246         28 |       274 
           |    100.00     100.00 |    100.00 


. tab socialmediaused urbancivic if startyear>1993, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
use of new |
    social |
     media |
(internet, |
    mobile |  Urban civic episode
  phones)? |        no        yes |     Total
-----------+----------------------+----------
        no |        25          4 |        29 
           |     55.56      15.38 |     40.85 
-----------+----------------------+----------
       yes |        20         22 |        42 
           |     44.44      84.62 |     59.15 
-----------+----------------------+----------
     Total |        45         26 |        71 
           |    100.00     100.00 |    100.00 


. tab newspaperused urbancivic if startyear>1993, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
    use of |
     print |
  material |
(newspaper |
        s, |
pamphlets, |  Urban civic episode
 leaflets? |        no        yes |     Total
-----------+----------------------+----------
        no |        22          9 |        31 
           |     48.89      34.62 |     43.66 
-----------+----------------------+----------
       yes |        23         17 |        40 
           |     51.11      65.38 |     56.34 
-----------+----------------------+----------
     Total |        45         26 |        71 
           |    100.00     100.00 |    100.00 


. tab radioused urbancivic if startyear>1993, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
    use of |  Urban civic episode
    radio? |        no        yes |     Total
-----------+----------------------+----------
        no |        27         16 |        43 
           |     60.00      61.54 |     60.56 
-----------+----------------------+----------
       yes |        18         10 |        28 
           |     40.00      38.46 |     39.44 
-----------+----------------------+----------
     Total |        45         26 |        71 
           |    100.00     100.00 |    100.00 


. tab televisused urbancivic if startyear>1993, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

Opposition |
    use of |
television |
       (or |
attempt to |
      gain |
   control |  Urban civic episode
      of)? |        no        yes |     Total
-----------+----------------------+----------
        no |        30         12 |        42 
           |     66.67      46.15 |     59.15 
-----------+----------------------+----------
       yes |        15         14 |        29 
           |     33.33      53.85 |     40.85 
-----------+----------------------+----------
     Total |        45         26 |        71 
           |    100.00     100.00 |    100.00 


. 
. * ====================================================
. * DIGITAL COMMUNICATIONS USAGE AMONG REV PARTICIPANTS
. * ====================================================
. * Ukrainian revolutions--internet and mobile phone usage among participants
. clear

. use monitoring20052014engmerged.dta

. tab internet newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |  Participated in rev
           |   protests vs. all
      Uses |   other respondents
  internet |         0          1 |     Total
-----------+----------------------+----------
        no |     1,393        222 |     1,615 
           |     91.64      79.57 |     89.77 
-----------+----------------------+----------
       yes |       127         57 |       184 
           |      8.36      20.43 |     10.23 
-----------+----------------------+----------
     Total |     1,520        279 |     1,799 
           |    100.00     100.00 |    100.00 


. tab internet newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |  Participated in rev
           |   protests vs. all
      Uses |   other respondents
  internet |         0          1 |     Total
-----------+----------------------+----------
        no |       676         47 |       723 
           |     41.22      30.32 |     40.28 
-----------+----------------------+----------
       yes |       964        108 |     1,072 
           |     58.78      69.68 |     59.72 
-----------+----------------------+----------
     Total |     1,640        155 |     1,795 
           |    100.00     100.00 |    100.00 


. tab mobilephone newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |  Participated in rev
      Owns |   protests vs. all
    mobile |   other respondents
     phone |         0          1 |     Total
-----------+----------------------+----------
         0 |     1,157        179 |     1,336 
           |     76.32      64.16 |     74.43 
-----------+----------------------+----------
         1 |       359        100 |       459 
           |     23.68      35.84 |     25.57 
-----------+----------------------+----------
     Total |     1,516        279 |     1,795 
           |    100.00     100.00 |    100.00 


. tab mobilephone newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

           |  Participated in rev
      Owns |   protests vs. all
    mobile |   other respondents
     phone |         0          1 |     Total
-----------+----------------------+----------
         0 |       196         21 |       217 
           |     11.97      13.55 |     12.10 
-----------+----------------------+----------
         1 |     1,442        134 |     1,576 
           |     88.03      86.45 |     87.90 
-----------+----------------------+----------
     Total |     1,638        155 |     1,793 
           |    100.00     100.00 |    100.00 


. tab digitaluser newpartica if EVA_vers=="yr2005", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

      Uses |
   digital |
communicat |
      ions |
technologi |
        es |  Participated in rev
(internet, |   protests vs. all
cellphone, |   other respondents
     etc.) |         0          1 |     Total
-----------+----------------------+----------
         0 |     1,113        163 |     1,276 
           |     73.42      58.63 |     71.13 
-----------+----------------------+----------
         1 |       403        115 |       518 
           |     26.58      41.37 |     28.87 
-----------+----------------------+----------
     Total |     1,516        278 |     1,794 
           |    100.00     100.00 |    100.00 


. tab digitaluser newpartica if EVA_vers=="yr2014", col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

      Uses |
   digital |
communicat |
      ions |
technologi |
        es |  Participated in rev
(internet, |   protests vs. all
cellphone, |   other respondents
     etc.) |         0          1 |     Total
-----------+----------------------+----------
         0 |       133         13 |       146 
           |      8.11       8.39 |      8.13 
-----------+----------------------+----------
         1 |     1,507        142 |     1,649 
           |     91.89      91.61 |     91.87 
-----------+----------------------+----------
     Total |     1,640        155 |     1,795 
           |    100.00     100.00 |    100.00 


. * Egyptian and Tunisian revolutions--internet and mobile phone usage among participants
. clear

. use fullarabbarom2.dta

. tab newinternet egrevpart if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

   Does or |
  does not |
       use |
  internet |    Participated in
    at all |  Egyptian rev (0/1)
     (0/1) |         0          1 |     Total
-----------+----------------------+----------
         0 |       936         44 |       980 
           |     83.65      48.89 |     81.06 
-----------+----------------------+----------
         1 |       183         46 |       229 
           |     16.35      51.11 |     18.94 
-----------+----------------------+----------
     Total |     1,119         90 |     1,209 
           |    100.00     100.00 |    100.00 


. tab newinternet trevpart if country==10, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

   Does or |
  does not |
       use |
  internet |    Participated in
    at all |  Tunisian rev (0/1)
     (0/1) |         0          1 |     Total
-----------+----------------------+----------
         0 |       671         63 |       734 
           |     69.68      36.84 |     64.73 
-----------+----------------------+----------
         1 |       292        108 |       400 
           |     30.32      63.16 |     35.27 
-----------+----------------------+----------
     Total |       963        171 |     1,134 
           |    100.00     100.00 |    100.00 


. 
. * ====================================================
. * CIVIL SOCIETY ASSOCIATION MEMBERS & INTERNET USAGE 
. *   AMONG PARTICIPANTS
. * ===================================================+
. * Ukrainian revolutions
. clear

. use monitoring20052014engmerged.dta

. tab civsoc internet if EVA_vers=="yr2005" & newpartica==1

Belongs to |
     civil |
   society |
associatio |     Uses internet
   n (0/1) |        no        yes |     Total
-----------+----------------------+----------
        no |       170         48 |       218 
       yes |        52          9 |        61 
-----------+----------------------+----------
     Total |       222         57 |       279 


. tab civsoc internet if EVA_vers=="yr2014" & newpartica==1

Belongs to |
     civil |
   society |
associatio |     Uses internet
   n (0/1) |        no        yes |     Total
-----------+----------------------+----------
        no |        38         72 |       110 
       yes |         9         36 |        45 
-----------+----------------------+----------
     Total |        47        108 |       155 


. * Egyptian and Tunisian revolutions
. clear

. use fullarabbarom2.dta

. tab membany newinternet if country==2 & egrevpart==1, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Are you a |
 member of |
       any |
organizati | Does or does not use
  on (from | internet at all (0/1)
    q501)? |         0          1 |     Total
-----------+----------------------+----------
     No/NA |        32         19 |        51 
           |     72.73      41.30 |     56.67 
-----------+----------------------+----------
       Yes |        12         27 |        39 
           |     27.27      58.70 |     43.33 
-----------+----------------------+----------
     Total |        44         46 |        90 
           |    100.00     100.00 |    100.00 


. tab membany newinternet if country==10 & trevpart==1, col 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 Are you a |
 member of |
       any |
organizati | Does or does not use
  on (from | internet at all (0/1)
    q501)? |         0          1 |     Total
-----------+----------------------+----------
     No/NA |        57         78 |       135 
           |     90.48      72.22 |     78.95 
-----------+----------------------+----------
       Yes |         6         30 |        36 
           |      9.52      27.78 |     21.05 
-----------+----------------------+----------
     Total |        63        108 |       171 
           |    100.00     100.00 |    100.00 


. 
. * =====================================================
. * ROLE OF CHURCH ATTENDANCE AMONG UNIATES IN FOSTERING 
. *   PARTICIPATION--EUROMAIDAN
. * =====================================================
. clear

. use monitoring20052014engmerged.dta

. logit newpartica gender newage i.uniate##i.attendschurch if EVA_vers=="yr2014", or

Iteration 0:   log likelihood = -523.02112  
Iteration 1:   log likelihood = -512.78811  
Iteration 2:   log likelihood = -478.79287  
Iteration 3:   log likelihood = -473.95183  
Iteration 4:   log likelihood = -473.81063  
Iteration 5:   log likelihood = -473.81061  

Logistic regression                             Number of obs     =      1,795
                                                LR chi2(5)        =      98.42
                                                Prob > chi2       =     0.0000
Log likelihood = -473.81061                     Pseudo R2         =     0.0941

--------------------------------------------------------------------------------------
          newpartica | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
              gender |   1.893326   .3416908     3.54   0.000     1.329254    2.696763
              newage |   .9868352   .0055789    -2.34   0.019     .9759611    .9978305
            1.uniate |   4.234158   1.485495     4.11   0.000     2.128801    8.421687
                     |
       attendschurch |
                yes  |   2.120879   .5535762     2.88   0.004     1.271574    3.537449
                     |
uniate#attendschurch |
              1#yes  |   1.157647   .5543141     0.31   0.760     .4528944    2.959072
                     |
               _cons |   .0817374   .0237339    -8.62   0.000     .0462657    .1444051
--------------------------------------------------------------------------------------

. margins i.uniate#attendschurch, atmeans

Adjusted predictions                            Number of obs     =      1,795
Model VCE    : OIM

Expression   : Pr(newpartica), predict()
at           : gender          =    .4423398 (mean)
               newage          =    45.77159 (mean)
               0.uniate        =     .924234 (mean)
               1.uniate        =     .075766 (mean)
               0.attendsc~h    =     .837883 (mean)
               1.attendsc~h    =     .162117 (mean)

--------------------------------------------------------------------------------------
                     |            Delta-method
                     |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------------+----------------------------------------------------------------
uniate#attendschurch |
               0#no  |   .0558057   .0061066     9.14   0.000      .043837    .0677745
              0#yes  |   .1113896   .0229976     4.84   0.000     .0663152     .156464
               1#no  |   .2001638   .0538391     3.72   0.000     .0946412    .3056864
              1#yes  |   .3805886   .0540761     7.04   0.000     .2746015    .4865757
--------------------------------------------------------------------------------------

. 
. * =====================================
. * FACEBOOK USAGE AMONG YOUNG TUNISIANS
. * =====================================
. clear

. use fullarabbarom2.dta

. tab te4113  if country==10 & newage<=25, m

  Are you a member |
 of or participant |
  in  3.A Facebook |
              page |      Freq.     Percent        Cum.
-------------------+-----------------------------------
               Yes |        160       63.24       63.24
                No |         18        7.11       70.36
                 . |         75       29.64      100.00
-------------------+-----------------------------------
             Total |        253      100.00

. tab te4113  if country==10 & newage>25, m

  Are you a member |
 of or participant |
  in  3.A Facebook |
              page |      Freq.     Percent        Cum.
-------------------+-----------------------------------
       Unspecified |          1        0.11        0.11
               Yes |        173       18.35       18.45
                No |         58        6.15       24.60
                 . |        711       75.40      100.00
-------------------+-----------------------------------
             Total |        943      100.00

. 
. * =====================================================
. * USE OF INTERNET, TV BY PARTICIPANTS TO FOLLOW EVENTS 
. *   OF REVOLUTION (TUNISIA AND EGYPT)
. * =====================================================
. clear

. use fullarabbarom2.dta

. tab eg807 egrevpart if country==2, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

  What source did you |
     depend onmost to |    Participated in
follow the revolution |  Egyptian rev (0/1)
         Jan25-Feb11? |         0          1 |     Total
----------------------+----------------------+----------
          Unspecified |         1          0 |         1 
                      |      0.09       0.00 |      0.08 
----------------------+----------------------+----------
                   TV |     1,071         73 |     1,144 
                      |     95.54      81.11 |     94.47 
----------------------+----------------------+----------
                Radio |         9          1 |        10 
                      |      0.80       1.11 |      0.83 
----------------------+----------------------+----------
Newspapers (the daily |        13          2 |        15 
                      |      1.16       2.22 |      1.24 
----------------------+----------------------+----------
         The internet |        10          8 |        18 
                      |      0.89       8.89 |      1.49 
----------------------+----------------------+----------
             Facebook |         5          4 |         9 
                      |      0.45       4.44 |      0.74 
----------------------+----------------------+----------
               E-mail |         0          1 |         1 
                      |      0.00       1.11 |      0.08 
----------------------+----------------------+----------
I don't follow anythi |         5          0 |         5 
                      |      0.45       0.00 |      0.41 
----------------------+----------------------+----------
Neighbors and friends |         3          0 |         3 
                      |      0.27       0.00 |      0.25 
----------------------+----------------------+----------
  Attending protests  |         0          1 |         1 
                      |      0.00       1.11 |      0.08 
----------------------+----------------------+----------
        I don�t know  |         4          0 |         4 
                      |      0.36       0.00 |      0.33 
----------------------+----------------------+----------
                Total |     1,121         90 |     1,211 
                      |    100.00     100.00 |    100.00 


. tab t907 trevpart if country==10, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

 What sources did you |
  depend on to follow |    Participated in
the revolution 17 Dec |  Tunisian rev (0/1)
    2010-14 Jan 2011? |         0          1 |     Total
----------------------+----------------------+----------
                   TV |       814        108 |       922 
                      |     82.81      63.16 |     79.90 
----------------------+----------------------+----------
                Radio |        22          4 |        26 
                      |      2.24       2.34 |      2.25 
----------------------+----------------------+----------
Newspapers (the daily |         5          0 |         5 
                      |      0.51       0.00 |      0.43 
----------------------+----------------------+----------
         The internet |        16          7 |        23 
                      |      1.63       4.09 |      1.99 
----------------------+----------------------+----------
             Facebook |        85         49 |       134 
                      |      8.65      28.65 |     11.61 
----------------------+----------------------+----------
              Twitter |         1          0 |         1 
                      |      0.10       0.00 |      0.09 
----------------------+----------------------+----------
               E-mail |         1          0 |         1 
                      |      0.10       0.00 |      0.09 
----------------------+----------------------+----------
   Declined to answer |         6          0 |         6 
                      |      0.61       0.00 |      0.52 
----------------------+----------------------+----------
         I don�t know |        23          2 |        25 
                      |      2.34       1.17 |      2.17 
----------------------+----------------------+----------
               Others |        10          1 |        11 
                      |      1.02       0.58 |      0.95 
----------------------+----------------------+----------
                Total |       983        171 |     1,154 
                      |    100.00     100.00 |    100.00 


. 
. * ==================================================
. * INTERNET USAGE AND PARTICIPATION W. FRIENDS AMONG 
. *   PARTICIPANTS (TUNISIA AND EGYPT)
. * ==================================================
. clear

. use fullarabbarom2.dta

. tab frpart egrevpart, col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Did |
friends/ac |
quaintance |
         s |
participat |
      e in |    Participated in
protests(q |  Egyptian rev (0/1)
 806/905)? |         0          1 |     Total
-----------+----------------------+----------
        no |       857         12 |       869 
           |     76.45      13.33 |     71.76 
-----------+----------------------+----------
       yes |       264         78 |       342 
           |     23.55      86.67 |     28.24 
-----------+----------------------+----------
     Total |     1,121         90 |     1,211 
           |    100.00     100.00 |    100.00 


. tab frpart trevpart , col

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Did |
friends/ac |
quaintance |
         s |
participat |
      e in |    Participated in
protests(q |  Tunisian rev (0/1)
 806/905)? |         0          1 |     Total
-----------+----------------------+----------
        no |       661         20 |       681 
           |     67.24      11.70 |     59.01 
-----------+----------------------+----------
       yes |       322        151 |       473 
           |     32.76      88.30 |     40.99 
-----------+----------------------+----------
     Total |       983        171 |     1,154 
           |    100.00     100.00 |    100.00 


. tab frpart intnetinrev if egpartic5==1, col chi 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Did |
friends/ac |
quaintance |
         s |
participat | Used internet during
      e in |  revolution [EG805,
protests(q | T904==1; EG807,T907]
 806/905)? |        no        yes |     Total
-----------+----------------------+----------
        no |        11          1 |        12 
           |     18.33       3.33 |     13.33 
-----------+----------------------+----------
       yes |        49         29 |        78 
           |     81.67      96.67 |     86.67 
-----------+----------------------+----------
     Total |        60         30 |        90 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =   3.8942   Pr = 0.048

. tab frpart intnetinrev if tpartic4==1, col chi 

+-------------------+
| Key               |
|-------------------|
|     frequency     |
| column percentage |
+-------------------+

       Did |
friends/ac |
quaintance |
         s |
participat | Used internet during
      e in |  revolution [EG805,
protests(q | T904==1; EG807,T907]
 806/905)? |        no        yes |     Total
-----------+----------------------+----------
        no |        17          3 |        20 
           |     18.89       3.70 |     11.70 
-----------+----------------------+----------
       yes |        73         78 |       151 
           |     81.11      96.30 |     88.30 
-----------+----------------------+----------
     Total |        90         81 |       171 
           |    100.00     100.00 |    100.00 

          Pearson chi2(1) =   9.5182   Pr = 0.002

. 
. * ==============================================
. * FIGURE 7.13:  STRONG TIES AND USE OF INTERNET 
. *   DURING REVOLUTIONS--ARAB REVS ONLY
. * ==============================================
. * Egypt
. mlogit egpartic5 gender c.newage##c.newage  frpart intnetinrev  if country==2, rrr

Iteration 0:   log likelihood = -1211.6406  
Iteration 1:   log likelihood = -1143.1739  
Iteration 2:   log likelihood = -1119.3876  
Iteration 3:   log likelihood = -1109.8018  
Iteration 4:   log likelihood = -1092.1804  
Iteration 5:   log likelihood =  -1075.519  
Iteration 6:   log likelihood = -1073.9532  
Iteration 7:   log likelihood = -1073.9512  
Iteration 8:   log likelihood = -1073.9511  

Multinomial logistic regression                 Number of obs     =      1,211
                                                LR chi2(20)       =     275.38
                                                Prob > chi2       =     0.0000
Log likelihood = -1073.9511                     Pseudo R2         =     0.1136

-----------------------------------------------------------------------------------
        egpartic5 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
Participate       |
           gender |   3.565495   1.003009     4.52   0.000     2.054322    6.188297
           newage |   1.139514   .0692751     2.15   0.032     1.011515    1.283711
                  |
c.newage#c.newage |   .9983464   .0007258    -2.28   0.023     .9969248      .99977
                  |
           frpart |   17.83013   5.972169     8.60   0.000     9.247965     34.3766
      intnetinrev |   3.875754   1.277273     4.11   0.000     2.031603      7.3939
            _cons |   .0007722   .0009837    -5.63   0.000     .0000636    .0093778
------------------+----------------------------------------------------------------
Aid               |
           gender |   1.257258   .5111657     0.56   0.573     .5666958    2.789324
           newage |   1.178375   .1145961     1.69   0.091     .9738788    1.425812
                  |
c.newage#c.newage |   .9983179   .0011034    -1.52   0.128     .9961576    1.000483
                  |
           frpart |   12.59985   6.505038     4.91   0.000     4.580446    34.65955
      intnetinrev |    3.72654   1.920315     2.55   0.011     1.357297    10.23144
            _cons |   .0001794   .0003786    -4.09   0.000     2.86e-06    .0112329
------------------+----------------------------------------------------------------
Support           |  (base outcome)
------------------+----------------------------------------------------------------
Apathetic         |
           gender |   1.021234   .2401345     0.09   0.929     .6441285    1.619117
           newage |   .9947896   .0466446    -0.11   0.911      .907443    1.090544
                  |
c.newage#c.newage |   1.000191   .0005176     0.37   0.712     .9991773    1.001206
                  |
           frpart |   .7362015   .2256665    -1.00   0.318     .4037192    1.342499
      intnetinrev |   6.37e-08   .0001603    -0.01   0.995            0           .
            _cons |   .0924654   .0914898    -2.41   0.016     .0132971    .6429835
------------------+----------------------------------------------------------------
Oppose            |
           gender |   .6809709   .1163056    -2.25   0.024     .4872464    .9517183
           newage |   .9548926   .0326299    -1.35   0.177     .8930337    1.021036
                  |
c.newage#c.newage |   1.000466   .0003924     1.19   0.235     .9996971    1.001235
                  |
           frpart |   .6319432   .1410148    -2.06   0.040     .4080721    .9786315
      intnetinrev |   1.121848   .5294297     0.24   0.808     .4448661    2.829036
            _cons |   .7471496   .5124452    -0.42   0.671     .1948034     2.86562
-----------------------------------------------------------------------------------

. margins, atmeans at(frpart=(0 1) intnetinrev=(0 1))

Adjusted predictions                            Number of obs     =      1,211
Model VCE    : OIM

1._predict   : Pr(egpartic5==Participate), predict(pr outcome(1))
2._predict   : Pr(egpartic5==Aid), predict(pr outcome(2))
3._predict   : Pr(egpartic5==Support), predict(pr outcome(3))
4._predict   : Pr(egpartic5==Apathetic), predict(pr outcome(4))
5._predict   : Pr(egpartic5==Oppose), predict(pr outcome(5))

1._at        : gender          =    .5028902 (mean)
               newage          =    39.45334 (mean)
               frpart          =           0
               intnetinrev     =           0

2._at        : gender          =    .5028902 (mean)
               newage          =    39.45334 (mean)
               frpart          =           0
               intnetinrev     =           1

3._at        : gender          =    .5028902 (mean)
               newage          =    39.45334 (mean)
               frpart          =           1
               intnetinrev     =           0

4._at        : gender          =    .5028902 (mean)
               newage          =    39.45334 (mean)
               frpart          =           1
               intnetinrev     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0143967   .0044796     3.21   0.001     .0056169    .0231766
        1 2  |   .0556339    .023361     2.38   0.017     .0098471    .1014207
        1 3  |   .2056996   .0329196     6.25   0.000     .1411785    .2702208
        1 4  |   .4551538   .0755069     6.03   0.000     .3071631    .6031446
        2 1  |     .00711   .0033533     2.12   0.034     .0005376    .0136823
        2 2  |   .0264176   .0174603     1.51   0.130    -.0078039    .0606391
        2 3  |   .0717874   .0204777     3.51   0.000     .0316519     .111923
        2 4  |   .1527294   .0578509     2.64   0.008     .0393437    .2661151
        3 1  |   .7479719   .0188539    39.67   0.000     .7110189    .7849248
        3 2  |   .7457707   .0704017    10.59   0.000      .607786    .8837554
        3 3  |    .599378   .0356129    16.83   0.000      .529578     .669178
        3 4  |   .3421916    .065337     5.24   0.000     .2141335    .4702497
        4 1  |   .0765915   .0114463     6.69   0.000     .0541572    .0990259
        4 2  |   4.86e-09   .0000122     0.00   1.000     -.000024     .000024
        4 3  |   .0451848    .012843     3.52   0.000     .0200131    .0703566
        4 4  |   1.64e-09   4.13e-06     0.00   1.000    -8.10e-06    8.10e-06
        5 1  |     .15393   .0159189     9.67   0.000     .1227296    .1851303
        5 2  |   .1721778   .0678938     2.54   0.011     .0391084    .3052472
        5 3  |   .0779501   .0159431     4.89   0.000     .0467022     .109198
        5 4  |   .0499251   .0221398     2.25   0.024     .0065319    .0933184
------------------------------------------------------------------------------

. * Tunisia
. mlogit tpartic4 gender newage  frpart intnetinrev  if country==10, rrr

Iteration 0:   log likelihood = -1030.2143  
Iteration 1:   log likelihood =  -901.4308  
Iteration 2:   log likelihood =  -877.3224  
Iteration 3:   log likelihood =  -876.4052  
Iteration 4:   log likelihood = -876.40278  
Iteration 5:   log likelihood = -876.40278  

Multinomial logistic regression                 Number of obs     =      1,154
                                                LR chi2(12)       =     307.62
                                                Prob > chi2       =     0.0000
Log likelihood = -876.40278                     Pseudo R2         =     0.1493

------------------------------------------------------------------------------------
          tpartic4 |        RRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
Participate        |
            gender |   4.544665    .999474     6.88   0.000     2.953272    6.993591
            newage |   .9815852   .0073757    -2.47   0.013     .9672349    .9961483
            frpart |   9.757791   2.540919     8.75   0.000     5.857327    16.25562
       intnetinrev |   2.112812   .4736116     3.34   0.001     1.361614    3.278443
             _cons |   .0298529   .0121558    -8.62   0.000     .0134396     .066311
-------------------+----------------------------------------------------------------
Support            |  (base outcome)
-------------------+----------------------------------------------------------------
Apathetic_inactive |
            gender |   1.026586   .1980864     0.14   0.892     .7033157    1.498442
            newage |   .9873577   .0066139    -1.90   0.058     .9744794    1.000406
            frpart |   .4307868    .104881    -3.46   0.001     .2673164    .6942232
       intnetinrev |   .8880006   .2742803    -0.38   0.701     .4847292    1.626774
             _cons |     .34056   .1027205    -3.57   0.000     .1885611    .6150849
-------------------+----------------------------------------------------------------
Oppose             |
            gender |   2.365988   .8202447     2.48   0.013     1.199269     4.66776
            newage |   .9764304   .0128219    -1.82   0.069     .9516206    1.001887
            frpart |   1.221756   .4351591     0.56   0.574     .6078659    2.455621
       intnetinrev |   2.176165   .8735358     1.94   0.053     .9908555    4.779398
             _cons |   .0568559   .0336466    -4.85   0.000     .0178257    .1813449
------------------------------------------------------------------------------------

. margins, atmeans at(frpart=(0 1) intnetinrev=(0 1))

Adjusted predictions                            Number of obs     =      1,154
Model VCE    : OIM

1._predict   : Pr(tpartic4==Participate), predict(pr outcome(1))
2._predict   : Pr(tpartic4==Support), predict(pr outcome(2))
3._predict   : Pr(tpartic4==Apathetic_inactive), predict(pr outcome(3))
4._predict   : Pr(tpartic4==Oppose), predict(pr outcome(4))

1._at        : gender          =    .5034662 (mean)
               newage          =    39.87955 (mean)
               frpart          =           0
               intnetinrev     =           0

2._at        : gender          =    .5034662 (mean)
               newage          =    39.87955 (mean)
               frpart          =           0
               intnetinrev     =           1

3._at        : gender          =    .5034662 (mean)
               newage          =    39.87955 (mean)
               frpart          =           1
               intnetinrev     =           0

4._at        : gender          =    .5034662 (mean)
               newage          =    39.87955 (mean)
               frpart          =           1
               intnetinrev     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_predict#_at |
        1 1  |   .0239648   .0055657     4.31   0.000     .0130562    .0348734
        1 2  |   .0486996   .0138728     3.51   0.000     .0215094    .0758899
        1 3  |   .2082645   .0241791     8.61   0.000     .1608744    .2556547
        1 4  |   .3495503   .0424692     8.23   0.000     .2663123    .4327884
        2 1  |   .7860794   .0165179    47.59   0.000      .753705    .8184538
        2 2  |   .7560614   .0407621    18.55   0.000     .6761692    .8359537
        2 3  |   .7000935   .0264808    26.44   0.000      .648192    .7519949
        2 4  |   .5561469   .0418316    13.29   0.000     .4741584    .6381354
        3 1  |   .1633212   .0150781    10.83   0.000     .1337687    .1928737
        3 2  |   .1394911   .0358904     3.89   0.000     .0691473     .209835
        3 3  |   .0626606   .0131537     4.76   0.000     .0368799    .0884413
        3 4  |    .044202   .0129686     3.41   0.001      .018784    .0696199
        4 1  |   .0266345   .0062511     4.26   0.000     .0143826    .0388865
        4 2  |   .0557478   .0214836     2.59   0.009     .0136407    .0978549
        4 3  |   .0289814   .0088009     3.29   0.001      .011732    .0462308
        4 4  |   .0501008    .016559     3.03   0.002     .0176457    .0825559
------------------------------------------------------------------------------

. 
. * =======================================================================
. * INTERNET USAGE AND CONSISTENCY OF PARTICIPATION IN EGYPTIAN REVOLUTION
. * =======================================================================
. clear

. use fullarabbarom2.dta

. poisson etotaldemos intnetinrev if country==2, irr

Iteration 0:   log likelihood =  -142.0083  
Iteration 1:   log likelihood =  -142.0083  

Poisson regression                              Number of obs     =         77
                                                LR chi2(1)        =       8.22
                                                Prob > chi2       =     0.0041
Log likelihood =  -142.0083                     Pseudo R2         =     0.0281

------------------------------------------------------------------------------
 etotaldemos |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
 intnetinrev |   1.514807   .2158941     2.91   0.004     1.145624    2.002962
       _cons |   2.283019   .2075472     9.08   0.000     1.910414    2.728296
------------------------------------------------------------------------------

. margins, at(intnetinrev=(0 1))

Adjusted predictions                            Number of obs     =         77
Model VCE    : OIM

Expression   : Predicted number of events, predict()

1._at        : intnetinrev     =           0

2._at        : intnetinrev     =           1

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   2.283019   .2075472    11.00   0.000     1.876234    2.689804
          2  |   3.458333   .3796014     9.11   0.000     2.714328    4.202338
------------------------------------------------------------------------------

. 
. 
. log close
      name:  <unnamed>
       log:  C:\Users\mbeissin\Desktop\Stata files for book\Logfiles\chapter7.log
  log type:  text
 closed on:  25 Jan 2022, 22:17:43
------------------------------------------------------------------------------------------------------------------
